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Optical fiber sensing plays a crucial role in modern measurement systems and holds significant promise for a wide range of applications. This potential, though, has been fundamentally constrained by the intrinsic latency and power…
Detecting and weighing the individual nanoparticles is an important approach to study the behavior and properties of single particles. Here we illustrate an effective mass sensing scheme using optomechanical resonator system. Based on the…
Atmosphere light value is a highly critical parameter in defogging algorithms that are based on an atmosphere scattering model. Any error in atmosphere light value will produce a direct impact on the accuracy of scattering computation and…
In the study of nuclear cross sections, the computational demands of data assimilation methods can become prohibitive when dealing with large data sets. We have developed a novel variant of the data thinning algorithm, inspired by the…
We present methods for efficient characterization of an optical coherent state $|\alpha\rangle$. We choose measurement settings adaptively and stochastically, based on data while it is collected. Our algorithm divides the estimation into…
We determine quantum precision limits for estimation of damping constants and temperature of lossy bosonic channels. A direct application would be the use of light for estimation of the absorption and the temperature of a transparent slab.…
Fiber optic sensing is becoming an important means to physically secure today's network infrastructure. However, a network-wide deployment of the monitors will require cost reduction of the interrogator system, which can only be achieved by…
We demonstrate an online (in-situ) sensor for continuous detection of oil contamination in compressed air systems complying with the ISO-8573 standard. The sensor is based on the photo-acoustic (PA) effect. The online and real-time PA…
Domain shift remains a persistent challenge in deep-learning-based computer vision, often requiring extensive model modifications or large labeled datasets to address. Inspired by human visual perception, which adjusts input quality through…
Viscosity measurement is essential for process monitoring and autonomous laboratory operation, yet conventional viscometers remain invasive and require controlled laboratory environments that differ substantially from real process…
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…
We analyze the observability of motion estimates from the fusion of visual and inertial sensors. Because the model contains unknown parameters, such as sensor biases, the problem is usually cast as a mixed identification/filtering, and the…
Biosensors are frequently used nowadays for the sake of their attractive capabilities. Because of their high accuracy and precision, they are more and more used in the medical sector. Natural receptors are mostly used, but their use have…
Insect populations are declining globally, making systematic monitoring essential for conservation. Most classical methods involve death traps and counter insect conservation. This paper presents a multisensor approach that uses AI-based…
Attaining the vision of Smart Cities requires the deployment of an enormous number of sensors for monitoring various conditions of the environment. Backscatter-sensors have emerged to be a promising solution due to the uninterruptible…
Accurate occupancy information helps to improve building energy efficiency and occupant comfort. Occupancy detection methods based on CO2 sensors have received attention due to their low cost and low intrusiveness. In naturally ventilated…
Temperature drift, stress birefringence and low frequency vibration lead to the randomness and fluctuation of the output of optical voltage sensor(OVS). In order to solve the problem, this study adopts the lock-in amplifier technology with…
The essential of navigation, perception, and decision-making which are basic tasks for intelligent robots, is to estimate necessary system states. Among them, navigation is fundamental for other upper applications, providing precise…
This thesis presents three studies in quantum-enhanced sensing and target detection. The first study explores covert target detection using optical or microwave probes, establishing quantum-mechanical limits on the error probabilities of…
Optimal experimental design is a classic topic in statistics, with many well-studied problems, applications, and solutions. The design problem we study is the placement of sensors to monitor spatiotemporal processes, explicitly accounting…