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Volatile organic compounds (VOCs) emitted by food products are considered markers for assessing quality of food. In this work, first-principles Density Functional Theory (DFT) and Non-equilibrium Green's function (NEGF) methods have been…
In-time and accurate assessments of on-road vehicle emissions play a central role in urban air quality and health policymaking. However, official insight is hampered by the Inspection/Maintenance (I/M) procedure conducted in the laboratory…
This paper addresses the environmental impacts linked to hazardous emissions from gas turbines, with a specific focus on employing various machine learning (ML) models to predict the emissions of Carbon Monoxide (CO) and Nitrogen Oxides…
Recommended standardized procedures for determining exhaled lower respiratory nitric oxide and nasal nitric oxide have been developed by task forces of the European Respiratory Society and the American Thoracic Society. These…
This paper proposes a machine learning-based methodology for the classification of various oil samples based on their dielectric properties, utilizing a microwave resonant sensor. The dielectric behaviour of oils, governed by their…
Air and water pollution are major threats to public health, highlighting the need for reliable environmental monitoring. Low-cost multisensor systems are promising but suffer from limited selectivity, because their responses are influenced…
A method for online decorrelation of chemical sensor signals from the effects of environmental humidity and temperature variations is proposed. The goal is to improve the accuracy of electronic nose measurements for continuous monitoring by…
Analyzing air pollution data is challenging as there are various analysis focuses from different aspects: feature (what), space (where), and time (when). As in most geospatial analysis problems, besides high-dimensional features, the…
This work focuses on the application related to the detection of low moisture and environmental pollutants. A novel gas sensor with inkjet printed Double Walled Carbon Nano Tubes (DWNTs) on a Love wave sensor platform was developed for…
This paper proposes a weakly-supervised machine learning-based approach aiming at a tool to alert patients about possible respiratory diseases. Various types of pathologies may affect the respiratory system, potentially leading to severe…
The nonlinear features of the relationships between concentrations of aerosol and volatile organic compounds (VOC) and oxides of nitrogen (NOx) in urban environments are derived directly from data of long-term routine measurements of NOx,…
Deep learning methods have been widely applied to visual and acoustic technology. In this paper, we proposed an odor labeling convolutional encoder-decoder (OLCE) for odor identification in machine olfaction. OLCE composes a convolutional…
Optical emission spectroscopy from a small-volume, 5 uL, atmospheric pressure RF-driven helium plasma was used in conjunction with Partial Least Squares Discriminant Analysis (PLS-DA) for the detection of trace concentrations of methane…
-This paper presents an inkjet printing capacitive microwave sensor for toxic vapor detection. The designed sensors were presented and fabricated with success. The experiments show sensitivity to ethanol vapor according to the S parameters.…
Emerging wireless technologies, such as 5G and beyond, are bringing new use cases to the forefront, one of the most prominent being machine learning empowered health care. One of the notable modern medical concerns that impose an immense…
A mid-infrared laser-based sensor is designed and demonstrated for trace detection of benzene, acetylene, and carbon dioxide at ambient conditions. The sensor is based on a distributed feedback quantum cascade lase and a multidimensional…
Diabetes is a global health burden, and early detection is critical for timely intervention. This study explores a non-invasive, data-driven framework to identify individuals at risk of diabetes using Volatile Organic Compounds (VOCs) and…
With the continuous development and improvement of medical services, there is a growing demand for improving diabetes diagnosis. Exhaled breath analysis, characterized by its speed, convenience, and non-invasive nature, is leading the trend…
Odor identification is an important area in a wide range of industries like cosmetics, food, beverages and medical diagnosis among others. Odor detection could be done through an array of gas sensors conformed as an electronic nose where a…
Plants emission of volatile organic compounds (VOCs) is involved in a wide class of ecological functions, as VOCs play a crucial role in plants interactions with biotic and abiotic factors. Accordingly, they vary widely across species and…