Electro-optically modulated lossy-mode resonance

Sensitivity, selectivity, reliability, and measurement range of a sensor are vital parameters for its wide applications. Fast growing number of various detection systems seems to justify worldwide efforts to enhance one or some of the parameters. Therefore, as one of the possible solutions, multi-domain sensing schemes have been proposed. This means that the sensor is interrogated simultaneously in, e.g., optical and electrochemical domains. An opportunity to combine the domains within a single sensor is given by optically transparent and electrochemically active transparent conductive oxides (TCOs), such as indium tin oxide (ITO). This work aims to bring understanding of electro-optically modulated lossy-mode resonance (LMR) effect observed for ITO-coated optical fiber sensors. Experimental research supported by numerical modeling allowed for identification of the film properties responsible for performance in both domains, as well as interactions between them. It has been found that charge carrier density in the semiconducting ITO determines the efficiency of the electrochemical processes and the LMR properties. The carrier density boosts electrochemical activity but reduces capability of electro-optical modulation of the LMR. It has also been shown that the carrier density can be tuned by pressure during magnetron sputtering of ITO target. Thus, the pressure can be chosen as a parameter for optimization of electro-optical modulation of the LMR, as well as optical and electrochemical responses of the device, especially when it comes to label-free sensing and biosensing.

Investigation of Widely Used SLAM Sensors Using Analytical Hierarchy Process

Applications of mobile robots are continuously capturing the importance in numerous areas such as agriculture, surveillance, defense, and planetary exploration to name a few. Accurate navigation of a mobile robot is highly significant for its uninterrupted operation. Simultaneous localization and mapping (SLAM) is one of the widely used techniques in mobile robots for localization and navigation. SLAM consists of front- and back-end processes, wherein the front-end includes SLAM sensors. These sensors play a significant role in acquiring accurate environmental information for further processing and mapping. Therefore, understanding the operational limits of the available SLAM sensors and data collection techniques from a single sensor or multisensors is noteworthy. In this article, a detailed literature review of widely used SLAM sensors such as acoustic sensor, RADAR, camera, Light Detection and Ranging (LiDAR), and RGB-D is provided. The performance of SLAM sensors is compared using an analytical hierarchy process (AHP) based on various key indicators such as accuracy, range, cost, working environment, and computational cost.

Assessing the quality of a network of vector-field sensors

An experiment consisting of a network of sensors can endow several advantages over an experiment with a single sensor: improved sensitivity, error corrections, spatial resolution, etc. However, there is often a question of how to optimally set up the network to yield the best results. Here, we consider a network of devices that measure a vector field along a given axis; namely for magnetometers in the Global Network of Optical Magnetometers for Exotic physics searches (GNOME). We quantify how well the network is arranged, explore characteristics and examples of ideal networks, and characterize the optimal configuration for GNOME. We find that by re-orienting the sensitive axes of existing magnetometers, the sensitivity of the network can be improved relative to the past science runs.

MULTIPARAMETRIC RECOGNITION OF ORGANIC VAPORS BY USING A GAS SENSOR BASED ON A NANOSTRUCTURED TIN DIOXIDE FILM

Исследовано влияние паров органических веществ (изопропанола, этанола и ацетона) различной концентрации на отклик сенсоров газа на основе наноструктурированных пленок диоксида олова, синтезированных золь-гель методом. Экспериментально установлено, что напуск газовых проб, содержащих пары органических веществ, приводит к увеличению проводимости наноструктурированных пленок диоксида олова. В области высоких концентраций (более 50% от насыщенного пара) концентрационная зависимость проводимости имеет тенденцию к насыщению. Показана возможность распознавания сорта примесного газа с помощью статистической обработки отклика только одного сенсора при различных концентрациях анализируемой пробы. Определено положение поверхностного донорного уровня примесного газа относительно акцепторного уровня кислорода и теплота десорбции частиц исследуемых газов. Предложен новый метод мультипараметрического распознавания газовых смесей, основанный на использование в качестве признаков классификации физико-химических параметров анализируемых газов, не зависящих от их концентрации. Установлено, что предложенный метод мультипараметрического распознавания газовых смесей имеет более высокую надежность по сравнению со стандартными методами, основанными на анализе отклика сенсоров газа. The influence of organic vapors (isopropanol, ethanol, and acetone) with different concentrations in air on a response gas sensor based on nanostructured tin dioxide films synthesized by the sol-gel method was studied. It was found experimentally that inject of the gas mixtures containing organic vapors into measure chamber results to an increase of the conductivity of nanostructured tin dioxide films. In the area of high concentrations (more than 50% of saturated vapor), the concentration dependence of conductivity trends to saturation. The recognizing possibility of species gas admixture by using statistical processing of response only single sensor at different analyzed gas mixture concentrations is validated. The surface donor level of gas-reducing relative to acceptor level oxygen and desorption heat of gas particle were determined. A new method based multiparametric recognition gas mixtures is proposed based on using concentration-independent physical and chemical parameters of analyzed gases as classification properties. It is shown that proposed multiparametric recognition method has higher reliability in comparison with standard methods based on the analysis gas sensor response.

Healing Seismic Data with Phase Corrections for Processing of Single-Sensor Data in the Desert Environment

Acquiring data with single sensors or small arrays in a desert environment may lead to challenging data quality for subsequent processing. We present a new approach to effectively "heal" such data and allow efficient processing and imaging without requiring any additional acquisition. A novel method combines the power of seismic beamforming and time-frequency masking originating from speech processing. First, we create an enhanced version of the data with beamforming or local stacking. Beamforming effectively suppresses scattered noise and finds weak reflection signals, albeit sacrificing some higher frequencies. Next, we employ a seismic time-frequency masking procedure to fix the original data while using beamformed data as a guide. Time-frequency masking effectively fixes corrupt and broken phase of the original data. After such data-driven healing, prestack data can be effectively processed and imaged, while maintaining the higher frequencies lost during beamforming.

Optimal sensor and actuator placement for feedback control of vortex shedding

We consider linear feedback control of the two-dimensional flow past a cylinder at low Reynolds numbers, with a particular focus on the optimal placement of a single sensor and a single actuator. To accommodate the high dimensionality of the flow, we compute its leading resolvent forcing and response modes to enable the design of $\mathcal {H}_2$ -optimal estimators and controllers. We then investigate three control problems: (i) optimal estimation (OE) in which we measure the flow at a single location and estimate the entire flow; (ii) full-state information control (FIC) in which we measure the entire flow but actuate at only one location; and (iii) the overall feedback control problem in which a single sensor is available for measurement and a single actuator is available for control. We characterize the performance of these control arrangements over a range of sensor and actuator placements and discuss implications for effective feedback control when using a single sensor and a single actuator. The optimal sensor and actuator placements found for the OE and FIC problems are also compared with those found for the overall feedback control problem over a range of Reynolds numbers. This comparison reveals the key factors and conflicting trade-offs that limit feedback control performance.