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Water-filling solutions play an important role in the designs for wireless communications, e.g., transmit covariance matrix design. A traditional physical understanding is to use the analogy of pouring water over a pool with fluctuating…
Wi-Fi sensing is an emerging technology that uses channel state information (CSI) from ambient Wi-Fi signals to monitor human activity without the need for dedicated sensors. Wi-Fi sensing does not only represent a pivotal technology in…
Accurate detection and analysis of traces of persistent organic pollutants in water is important in many areas, including environmental monitoring and food quality control, due to their long environmental stability and potential…
Water isotope separation, specifically separating heavy from light water, is a socially significant issue due to the usage of heavy water in applications such as nuclear magnetic resonance, nuclear power, and spectroscopy. Separation of…
As the complexity and scale of modern computer networks continue to increase, there has emerged an urgent need for precise traffic analysis, which plays a pivotal role in cutting-edge wireless connectivity technologies. This study focuses…
We study efficient deep learning training algorithms that process received wireless signals, if a test Signal to Noise Ratio (SNR) estimate is available. We focus on two tasks that facilitate source identification: 1- Identifying the…
Potential harms of Large Language Models such as mass misinformation and plagiarism can be partially mitigated if there exists a reliable way to detect machine generated text. In this paper, we propose a new watermarking method to detect…
We show how machine learning techniques based on Bayesian inference can be used to reach new levels of realism in the computer simulation of molecular materials, focusing here on water. We train our machine-learning algorithm using…
When employing underwater vehicles for the autonomous inspection of assets, it is crucial to consider and assess the water conditions. These conditions significantly impact visibility and directly affect robotic operations. Turbidity can…
We report the application of machine learning to smartphone based colorimetric detection of pH values. The strip images were used as the training set for Least Squares-Support Vector Machine (LS-SVM) classifier algorithms that were able to…
In this paper, we explore the use of multiple deep learning techniques to detect weak interference in WiFi networks. Given the low interference signal levels involved, this scenario tends to be difficult to detect. However, even…
In this article, we present a survey of recent advances in passive human behaviour recognition in indoor areas using the channel state information (CSI) of commercial WiFi systems. Movement of human body causes a change in the wireless…
Industry 4.0 will make manufacturing processes smarter but this smartness requires more environmental awareness, which in case of Industrial Internet of Things, is realized by the help of sensors. This article is about industrial…
Robust classification of the operational environment of wireless devices is becoming increasingly important for wireless network optimization, particularly in a shared spectrum environment. Distinguishing between indoor and outdoor devices…
This study proposes a Deep Belief Network model to classify traffic flow states. The model is capable of processing massive, high-density, and noise-contaminated data sets generated from smartphone sensors. The statistical features of…
The deep learning (DL)-based methods of low-level tasks have many advantages over the traditional camera in terms of hardware prospects, error accumulation and imaging effects. Recently, the application of deep learning to replace the image…
Strong authentication in an interconnected wireless environment continues to be an important, but sometimes elusive goal. Research in physical-layer authentication using channel features holds promise as a technique to improve network…
Accurate detection of human presence in indoor environments is important for various applications, such as energy management and security. In this paper, we propose a novel system for human presence detection using the channel state…
Detecting leaks in water networks is a costly challenge. This article introduces a practical solution: the integration of optical network with water networks for efficient leak detection. Our approach uses a fiber-optic cable to measure…
Monitoring water contaminants is of paramount importance, ensuring public health and environmental well-being. Turbidity, a key parameter, poses a significant problem, affecting water quality. Its accurate assessment is crucial for…