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A highly selective solid-state fluorescent sensor based on N-doped carbon quantum dots (N-CQDs) and cotton fiber paper (CFP) is reported for the determination of trace mercury (II)(Hg2+). The N-doped carbon quantum dots on cotton fiber paper (N-CQDs@CFP) was synthesized using a facile one-step microwave hydrothermal method. Multiple approaches were employed to fully investigate the morphology and chemical structure of the paper-based fluorescent sensor. The N-CQDs were chemically bonded onto the CFP, which offers good reproducibility and stability of the sensor. The N-CQDs@CFP showed high-intensity blue emission in dark-field imaging, and the fluorescence was quenched by Hg2+. The Hg2+ in aqueous samples was easily determined and visually monitored. There was good linearity from 0 to 250 μM, and the limit of detection was 34 nM. The paper-based fluorescent sensor provided accurate and rapid determination of Hg2+ upon comparison with flame atomic absorption spectrophotometry (FAAS). The simple preparation, rapid detection (< 5 min), low cost, and easy-handling illustrate that the reported sensor has a significant value in environmental monitoring. [ABSTRACT FROM AUTHOR]

In this study, carbon quantum dots (CQDs) and rhodamine B (RhB) were physically mixed to construct a highly selective and sensitive ratiometric fluorescent sensor (CQDs@RhB) for the quantitative and visual detection of Hg2+. After adding Hg2+, the emission peak of CQDs at 445 nm was quenched and the peak of RhB at 575 nm remained unchanged; the ratio of the two emission peaks had a linear relationship with the Hg2+ concentration. The CQDs@RhB had a detection range of 0–15 µM and the limit of detection (LOD) is 65.93 nM and a color change from blue to pink was visible to the naked eye under ultraviolet light. The study revealed a static quenching mechanism of CQDs@RhB. The established method was successfully applied to the detection of Hg2+ in real water and rice samples with satisfactory results. In addition, a portable fluorescent paper-based sensor platform was developed using computer software assistance. The relationship with Hg2+ concentration was constructed by converting the pictures obtained under ultraviolet light to RGB color mode for visualization and quantitative detection of Hg2+. This study provides a valuable strategy for constructing a rapid detection system for Hg2+ in the field. [ABSTRACT FROM AUTHOR]

A newly developed research topic, fabricated paper-based microfluidic sensors, was discussed in the field of low-cost environmental detection. Distinguished with the traditional dipstick or lateral-flow setups, these paper-based microfluidic sensors can serve as a tool for onsite quantitative and semi-quantitative measurements, without risks to cause environmental pollution. They have attracted increasing interest since the first easy-fabricated paper-based setup reported by Whitesides group in 2007. Most of the publications utilized paper-based sensors in clinical detection. In recent years, some groups started to use these sensors in environmental measurement, leading to precise, easy operation, low-cost, and eco-friendly methods for onsite detection. In this review, paper-based microfluidic sensors were briefly introduced, followed by literatures review and discussion for future perspectives. [ABSTRACT FROM AUTHOR]

In this study, carbon quantum dots (CQDs) and rhodamine B (RhB) were physically mixed to construct a highly selective and sensitive ratiometric fluorescent sensor (CQDs@RhB) for the quantitative and visual detection of Hg2+. After adding Hg2+, the emission peak of CQDs at 445 nm was quenched and the peak of RhB at 575 nm remained unchanged; the ratio of the two emission peaks had a linear relationship with the Hg2+ concentration. The CQDs@RhB had a detection range of 0–15 µM and the limit of detection (LOD) is 65.93 nM and a color change from blue to pink was visible to the naked eye under ultraviolet light. The study revealed a static quenching mechanism of CQDs@RhB. The established method was successfully applied to the detection of Hg2+ in real water and rice samples with satisfactory results. In addition, a portable fluorescent paper-based sensor platform was developed using computer software assistance. The relationship with Hg2+ concentration was constructed by converting the pictures obtained under ultraviolet light to RGB color mode for visualization and quantitative detection of Hg2+. This study provides a valuable strategy for constructing a rapid detection system for Hg2+ in the field. [ABSTRACT FROM AUTHOR]

There has been an increase in the discovery and usage of sensors for the detection of chemical compounds in the field of analytical chemistry since the last several years. This has led to progressive research in nanotechnology for developing efficient nanomaterials for bio-chemical sensing applications. Thereby, a deft synthesis of silver nanoparticles (Ag NPs) under microwave irradiation was achieved using sodium alginate as a reducing and capping agent in a fast and cost-effective approach. As per the X-ray diffraction analysis, the average particle size of Ag NPs was found to be 10 nm. X-ray photoelectron spectroscpopy analysis showed characteristic peaks at binding energies of 368.10 and 374.11 eV indicating the formation of Ag NPs. The synthesized Ag NPs-alginate composite was further used to develop a paper-based sensor for the detection of H2O2. Detection of H2O2 is based on the discolouration of the Ag NPs-alginate composite modified paper sensor as a function of H2O2 concentration. The analysis of the decoloured paper strips was done by a smartphone camera and an RGB Colour Reader application (app) to measure colour intensity. The sensing characteristics were found in the range of 0.1–10 mM. The colour analysis revealed piecewise linear relationship of intensity of RGB to H2O2 concentration in the range of 0.1–1.5 and 2–10 mM with R2 values of 0.97 and 0.9778, respectively. Owing to the high sensitivity, selectivity, and cost-effectiveness, the developed paper sensor can be a potential tool for real-time analysis of H2O2. [ABSTRACT FROM AUTHOR]

Microfluidic paper-based analytical devices (µPADs) have attracted much attention over the past decade because they offer clinicians the ability to deliver point-of-care testing and onsite analysis. Many of the advantages of µPADs, however, are limited to work in a laboratory setting due to the difficulties of processing data when using electronic devices in the field. This review focuses on the use of µPADs that have the potential to work without batteries or with only small and portable devices such as smartphones, timers, or miniaturized detectors. The µPADs that can be operated without batteries are, in general, those that allow the visual judgment of analyte concentrations via readouts that are measured in time, distance, count, or text. Conversely, a smartphone works as a camera to permit the capture and processing of an image that digitizes the color intensity produced by the reaction of an analyte with a colorimetric reagent. Miniaturized detectors for electrochemical, fluorometric, chemiluminescence, and electrochemiluminescence methods are also discussed, although some of them require the use of a laptop computer for operation and data processing. [ABSTRACT FROM AUTHOR]

2ʹ-(2-((4-(methylthio)phenyl)amino)-2-oxoethoxy)-[1,1ʹ-biphenyl]-2-yl 5(dimethyl amino)naphthalene-1-sulphonate (1) was synthesised and used as a F− ion sensor. The selectivity of sensor 1 with various anions (F−, Cl−, Br−, CH3COO−, C6H5COO− and H2PO4−) in DMSO was evaluated by 1H NMR, UV-visible and fluorescence study. For 1H NMR, an amide proton of sensor 1 disappeared due to the deprotonation reaction upon addition of F− ion. On the contrary, the proton signal of HF2− emerged at 16.11 ppm. Upon addition of F− ion, sensor 1 showed a new absorption band at 300 nm and the solution turned colourless. For fluorescence response, sensor 1 exhibited the enhancement of emission intensity at 434 nm with slight blue shift when titrated with F− ion. These results suggest that sensor 1 possessed high sensitivity and selectivity towards F− ion detection. In addition, the sensor 1 test strip coated on TLC plates and filter papers were demonstrated for specific detection F− ion. [ABSTRACT FROM AUTHOR]

In their paper on the last glaciation of Shetland, Golledge et al. (2008) concluded on the basis of a remote sensing study that during that period Shetland had been overrun by ice from Scandinavia. Since the method of study they used does not reveal the sense of the direction in which the ice flowed and since they ignored earlier ground-based work involving striations which do reveal the sense of direction of ice flow their conclusions have no scientific basis. [ABSTRACT FROM AUTHOR]

A sensor installation and evaluation programme at the Institute of Ocean Sciences, Sidney, BC, Canada, shows that the weather buoys operating round Canada's coasts can be used as important new sources of surface information for satellite sensor calibration and validation. The standard instruments on the buoys provide real-time measurements to forecasters--of wind, waves, water and air temperature and air pressure. The present programme is evaluating the addition of sensors measuring chlorophyll fluorescence, Photosynthetically Available Radiation (PAR), salinity and water-leaving radiance. Time-series of these data are also of value for a variety of fisheries, ecosystem and climate studies. Data can be viewed on the web at http://www-sci.pac.dfo-mpo.gc.ca/ecobuoys. [ABSTRACT FROM AUTHOR]

The technique of vicarious calibration is used in connection with an atmospheric correction to improve the Sea viewing Wide Field of view Sensor (SeaWiFS) normalized water-leaving radiance by the first determination of mean vicarious calibration coefficients from in situ measurements in the Baltic Sea. A necessary adjustment of the SeaWiFS pre-flight calibration slope was found to be +3.5%, +0.3%, -1.7%, -0.4%, +0.8% and -1.3% for the first six SeaWiFS channels. The derived mean vicarious calibration coefficients are higher than the coefficients in the standard SeaWiFS Data Analysis System (SeaDAS) software but with similar shape and good agreement with other research results. The coefficients were used to obtain better normalized water-leaving radiance from SeaWiFS measurements in the Baltic Sea. The deviations of calculated to measured radiances in the open Baltic Sea are between 3% and 47% in the channels 412 to 670 nm, with the trend of higher deviations in the blue channels. The objective of radiance determination in all SeaWiFS channels with a maximum uncertainty of 5% in clear water regions is probably not reachable in the turbid water of the Baltic Sea. [ABSTRACT FROM AUTHOR]

Synoptic coverage of the temporal and spatial variability of aerosol distribution patterns can only be achieved with satellites. Results from the first ocean colour sensor, the Coastal Zone Color Scanner (CZCS), indicate an annual cycle of the major mineral aerosol plumes that is consistent with the published literature. Seasonality and interannual aerosol variability observed with the CZCS agrees well with that found by ground data measurements and other satellite platforms used to monitor aerosols. The successor to the CZCS--the Sea viewing Wide Field of view Sensor (SeaWiFS)--provides estimates of aerosol load and particle size, both on a global scale. Seasonal maps of both of these aerosol optical properties are in accord with well-known distribution patterns and also with independent satellite estimates. These results indicate that ocean colour sensors are capable of monitoring the variability of global aerosol loads and, more recently, with the retrieval of aerosol particle size, they can be used to characterize different aerosol events. [ABSTRACT FROM AUTHOR]

The salinity of the open ocean is important for understanding ocean dynamics and for modelling energy exchange with the atmosphere. But existing data are sparse and much of the ocean is unsampled. Sea surface salinity can be measured remotely with passive microwave sensors operating near 1.4 GHz (L-band). Salinity differences have been observed from space and aircraft instruments have demonstrated that salinity can be measured with an accuracy of better than 1 psu. Sensor technology has improved sufficiently to seriously propose a satellite system to map salinity over the open oceans. [ABSTRACT FROM AUTHOR]

For the year 1999 all Sea viewing Wide Field of view Sensor (SeaWiFS) scenes of the Danish waters from the North Sea to the Baltic Sea were browsed, and a total of 47 SeaWiFS scenes with reasonably low cloud cover and, therefore, potential in situ match-ups were found and processed. The in situ data used as match-ups were collected on routine monitoring cruises by Danish and Swedish environmental authorities. A few stations in the North Sea, Skagerak and the western Baltic Sea were sampled, while most stations were located in Kattegat and the inner Danish waters. A turbid water SeaWiFS atmospheric correction algorithm was applied, since the standard SeaWiFS algorithm for chlorophyll- a (CHL) has been shown to be fairly inaccurate in turbid coastal waters. This is due to both inaccurate atmospheric and to relatively high and variable abundance of yellow substance. The application of the turbid atmospheric correction substantially improved the SeaWiFS CHL estimates. Regressions between SeaWiFS estimates using the OC2 and OC4 algorithms used in the SeaDAS software (versions 3.3 and 4.0, respectively) and in situ CHL values were made as well, and regression with a number of other possible reflectance ratios with SeaWiFS channels. The best correlation was found to be R 2 =0.54 using a double-ratio algorithm using both R510/R555 and R443/R670, while the OC4v4 had the second best correlation of R 2 =0.39. Among other single ratios, the R510/R555 had the highest correlation with CHL, which was expected since this is also the ratio that OC4v4 most often switches to in the waters investigated here. The range of CHL concentrations in this study was rather limited (all but three points from 0.5-3 mg m -3 ) so there is a need for inclusion of more data to expand the concentration range. This should be possible using also data from 2000, 2001 and onwards and, hereafter, a more 'stable' empirical algorithm can be derived for the Danish waters. [ABSTRACT FROM AUTHOR]

The National Aeronautics & Space Administration (NASA) Sea viewing Wide Field of view Sensor (SeaWiFS) began operational measurement of ocean colour in September 1997. Upgrades to the SeaWiFS data processing system (SeaDAS) have occurred frequently and the effects of these revisions on the remotely sensed estimates of chlorophyll- a concentration (chl- a ) have been significant. Measurements of chl- a from research work in the Bay of Biscay and Gulf of Cadiz during 1998-1999 are used to validate the SeaWiFS chl- a product generated using the current version of SeaDAS (version 4.1). The validation data cover coastal and offshore waters, including those dominated by inorganic suspended sediment, and an intense dinoflagellate bloom where shipboard chl- a measurements exceeded 50 mg m -3 . The standard SeaWiFS chlorophyll algorithm (OC4v4) generally performed well, but significantly over-estimated chl- a where inorganic suspended sediment was present. The algorithm is only applicable to chl- a values up to 64 mg m -3 , which was less than chl- a at the centre of the bloom. A novel algorithm for chl- a , which first estimates the inherent optical properties of the water, was applied to the SeaWiFS measurements but failed on over 90% of the pixels, perhaps because SeaWiFS is under-estimating water reflectance at the extreme blue end of the visible spectrum. [ABSTRACT FROM AUTHOR]

This research investigates the double tracking control problem for the complex dynamic network (CDN) with an unavailable link state. Firstly, from the angle of a large-scale system, the dynamical model of CDN is described by the vector differential equations, which consists of node dynamic subsystem (NDS) and link dynamic subsystem (LDS), in which the weighted-values of links are regarded as the state variables of LDS. Secondly, to realise the double tracking control (DT-Control) of CDN, the presented DT-Control scheme in this paper includes the synthesis of controller for NDS and the coupling term in LDS, which can ensure that the two subsystems track the given reference targets. The tracking of NDS contains the synchronisation of nodes as the special case, and the tracking of LDS shows that the eventual topologic structure of CDN will be determined only by the given link reference signal. Due to the economic and technological limitations of sensors in the practice applications, this paper assumes that the state variables of LDS are unavailable in the DT-Control scheme. Finally, the engineering simulation example is given to verify the validity of DT-Control scheme proposed in this paper. [ABSTRACT FROM AUTHOR]

Dynamic origin–destination (OD) flow is a fundamental input for dynamic network models and simulators. Numerous studies have conducted dynamic OD estimations based on fixed detectors, where a high device coverage rate and data quality are often required to accomplish the desired results. Several existing methods have used probe vehicle trajectories as an additional data source, and generalized least squares (GLS) is commonly recognized as an effective framework. However, the prior matrices used in these models either came from historical data or data obtained by uniform scaling that neglected the variation in penetration rates and suffer from sparsity issues. Moreover, the microscopic information contained in the high-resolution probe vehicle trajectories has not been fully utilized. The possibility of estimating OD flows using only vehicle trajectories without external information is rarely discussed in current literature. Therefore, this paper introduces a dynamic OD flow estimation model solely using probe vehicle trajectories. In the proposed model, two methods based on probe OD pair distribution are proposed to infer prior OD flows. Then the GLS framework is extended by including link travel times as another objective term, and the solution algorithm is adapted to deal with uncertain priors. To validate the proposed model, extensive experiments were conducted on a simulation network. The results show that the proposed model could reliably estimate dynamic OD flows and showed superiority to two existing models. In sensitivity analysis concerning the penetration rate and degree of saturation, the proposed model presented satisfactory performance and could adapt to various conditions. [ABSTRACT FROM AUTHOR]

To compete with e-commerce, retailers are increasingly integrating smart technologies into their offline retail environment. This enables retailers to analyze their customers and provide them with a personalized shopping experience. However, research to date has mainly focused on the customer rather than the retailer. Building on a semi-systematic review of 75 studies using sensor technologies in retail environments between 2001 and 2021, this paper facilitates future research on the selection and combination of sensor technologies for in-store customer analysis from a retailer's perspective. The literature was analyzed in terms of the technology used, the raw data collected, and the interpretation of the data. The results show that technologies were primarily used to gain insights into customers' physical behavior, while few studies attempted to identify the customer or examine customers' emotions. The identified studies rarely combined multiple technologies. Based on the analysis, this study provides recommendations for selecting and combining sensor technologies in stores. Current approaches to support technology selection take a broad perspective and compare entire store technology concepts, such as smart shelving or smart shopping carts, rather than basic sensor technologies. The findings are relevant to both research and retail practice. [ABSTRACT FROM AUTHOR]

In this paper, a recursive filtering problem is analyzed for nonlinear systems with sensor saturation under duty cycle scheduling (DCS). The sensor saturation is taken into account to describe practical engineering better. The DCS is introduced to conserve energy by alternating sensor nodes between active and dormant states. The considered problem aims to design a collaboration-prediction-based recursive filtering algorithm for nonlinear systems with sensor saturation such that, under the sparse measurements due to DCS, satisfactory filtering performance is guaranteed. By solving a set of matrix difference equations, the upper bound on the filtering error covariance is first obtained, and then the gain matrix of the filter that minimizes the upper limit is calculated. In addition, the boundedness of the upper bound of the filtering error covariance is analyzed. Finally, the effectiveness of the proposed collaboration-prediction-based recursive filtering algorithm is verified by the simulation example. [ABSTRACT FROM AUTHOR]

The Greenhouse Gas Monitoring Instrument (GMI) onboard the Chinese hyperspectral satellite GF5–02 can provide abundant observations of global atmospheric CO2, which plays an important role in climate research. CO2 retrieval precision is the key to determining the application value of the GMI. To reduce the influence of atmospheric scattering on retrieval, we combined the Directional Polarimetric Camera (DPC) data on the same satellite to improve the anti-interference ability of GMI CO2 retrieval and ensure its retrieval precision. To realize the reliability and feasibility of the collaborative use of the GMI and DPC, this paper designs the pointing registration method of the GMI based on coastline observations, the spatial resolution matching method and the collaborative cloud screening method of the GMI and DPC observations. Combined with the DPC, which supplied the spectral data and aerosol product, the retrieval ability of the coupled bidirectional reflectance distribution function CO2 retrieval (CBCR) method developed for GMI CO2 retrieval was improved, with the retrieval efficiency of CO2 products increasing by 27%, and the CO2 retrieval precision increasing from 3.3 ppm to 2.7 ppm. Moreover, collaborative use not only guaranteed the GMI's ability to detect global and area CO2 concentration distribution characteristics, such as significant concentration differences between the Northern and Southern Hemispheres in winter and high CO2 concentrations in urban agglomeration areas caused by human activities, but also extended the GMI's potential for monitoring anomalous events, such as the Tonga volcanic eruption. [ABSTRACT FROM AUTHOR]

In the multi-target scenarios, we consider the problem of constant false alarm rate (CFAR) target detection. For the conventional CFAR algorithms, the multi-target detection performance is mainly limited by the interference target tolerance within the reference window. In this paper, we propose a local ordered statistic CFAR (OS-CFAR) target detector based on compressed sensing (CS) radar system to address the degradation of detection performance in multi-target scenarios. With the analog-information-converter (AIC), the radar intermediate frequency (IF) signal is compressively sampled into discrete linear measurements. At each detection stage, multiple signal components are generated by correlation tests between the sensing matrix and linear measurements. By support set merge and proxy pruning, the signal components with the largest energy are retained. These components are the echoes reflected from the targets. Since target components are output in decreasing order of correlation, the proposed detector only requires a local OS-CFAR decision in the interval where the least correlated target is located, rather than traversing the entire interval. By continuously updating the detection stage, all targets that satisfy the false alarm rate requirement can be screened out. Finally, the performance of the proposed detector in the multi-target scenarios is confirmed by simulation results. [ABSTRACT FROM AUTHOR]

This paper describes a novel method for the estimation of the trajectory and orientation of a rigid body moving along a railway track. Compared to other recent developments in the literature, the presented approach has the significant advantage of using inertial sensors only, excluding global position and orientation sensors. The excluded sensors are compensated with an odometry system and previous knowledge of the design track geometry. The procedure is based on a kinematic model of the relative motion of the body with respect to the track, together with a Kalman filter algorithm. Two different approaches are used and compared for the estimation of the noise covariance matrices in the Kalman filter. One is based on the use of experimental results with a known output. The other one relies upon constrained maximum likelihood estimation. The calculated trajectory and orientation are applied in this research to the problem of track geometry measurement. A scale track is used for experimental validation, showing that results are sufficiently accurate for this application. The obtained results also reveal that the constrained maximum likelihood estimation performs similarly to the known-output method. This is very convenient because it allows a straightforward application of the algorithm in different scenarios. [ABSTRACT FROM AUTHOR]

This paper investigates the secure state estimation problem of the cyber-physical systems (CPSs) in the presence of malicious attacks. Considering the destructiveness and stealthiness of the attacker, a novel stochastic transmission scheme, in which the repeater generates transmission data by randomly combining some measurement values, is proposed to ensure the effectiveness of the attack detector. A filter equipped with the $ \chi ^2 $ χ 2 detector and the stochastic transmission scheme is proposed to conduct the secure state estimation. The attack probability condition of the estimation error being mean-square bounded is given, which indicates that stochastic transmission scheme has a limited effect on the filter. Some numerical simulations are given to illustrate the effectiveness of the proposed transmission scheme. [ABSTRACT FROM AUTHOR]

In this paper, a new three-dimensional network coordination polymer {[Co(TPTC)(HBPDPE)2·2H2O]·3H2O}n [[[(1:1′:4′,1″-terphenyl)-3,3″,5,5″-tetracarboxylic cobalt (II)] dipyridine dihydrate] trihydrate] (Complex 1) was generated under solvothermal synthesis by rigid conjugated ligand H4TPTC ([1:1′:4′,1″-terphengl]-3,3″,5,5″-tetracarboxylic), V-shaped BPDPE (4,4′-bis (pyridyl) diphenyl ether) and Co(II) ion. In complex 1, the neighboring Co(II) ions are linked by deprotonated TPTC4- to achieve a 1D zigzag chain [Co(TPTC)(HBPDPE)2]n, then the adjacent [Co(TPTC)(HBPDPE)2]n chains linked each other by various H-bondings to extend the structure from 1D chain to 3D network. Complex 1 has excellent fluorescence sensing performance and exhibits high sensitivity and selectivity for detecting 2,4,6-trinitrophenol (TNP), the quenching constant Ksv is up to 2.08 × 105 M−1 along with the correlation coefficient R2 of 0.993. Furthermore, the quench mechanisms of this Co-MOF as a sensor to detect nitro- aromatic explosives were studied as well. A new three-dimensional coordination polymer {[Co(TPTC)(HBPDPE)2·2H2O]·3H2O}n (1), constructed by 1D zigzag chains and H-bondings interactions, was synthesized under solvothermal condition by a rigid conjugated ligand H4TPTC ([1:1′:4′,1″-terphengl]-3,3″,5,5″-tetracarboxylic), BPDPE (4,4′-bis (pyridyl) diphenyl) and Co(II) ion. Complex 1 has excellent fluorescence sensing performance for detecting Nitroaromatic explosive (NAE) 2,4,6-trinitrophenol (TNP), the quenching constant Ksv is up to 2.08 × 105 M−1, and the quenching mechanism was studied as well. [ABSTRACT FROM AUTHOR]

Profile monitoring faces great challenges on account of the rapid development of advanced sensor technology. Massive sensor data are highly correlated and change in a complex way over time, which are difficult to describe with parametric models. Furthermore, quality characteristics are often affected by covariates. In this paper, nonparametric monitoring schemes considering covariates are proposed to monitor the correlated profiles in real-time. A profile model considering covariates based on Gaussian process is developed to predict the expected profile. Two control charts are then constructed based on the differences between the observed and expected profiles, which are calculated by Euclidean distance and definite integral, respectively. The effectiveness of the proposed monitoring schemes is validated by simulations. The proposed schemes are applied to a real case of busbar state monitoring in an automotive manufacturing plant. [ABSTRACT FROM AUTHOR]

A simple dipole antenna maybe not intended to measure the transient electromagnetic pulse of sharp rise time in order of picoseconds. The pulse might be produced from numerous ways and their particular recognition is a need for proficient innovative work of the related systems. Magnetic-field sensor (B-dot) and Electric-field sensor (D-dot) are the more suited choice for precise detection of such pulse, owing to their pungent rise time. In this paper, the new conceptualized design of the B-dot sensor using a Mobius loop and detailed design of the Ground Plane D-dot sensors using an Equivalent Charge Distribution Method, followed by the principal, configuration, and calibration methods are introduced. Furthermore, an advanced prototype of the electric field sensor is developed based on simulation analysis and lightweight Aluminum (Al) Alloy. Moreover, the paper emphasizes the consequence of material choice on bandwidth and technically deployment of Al-Alloy in sensor manufacturing. The developed prototype is up to 3.0 times lesser in weight and up to 3.0 times, economical compared to a like Copper-based sensor and has a bandwidth greater than 12.1 GHz, which minimize multi-sensor requirement in the measurement of the electromagnetic pulse with wide-band EM systems. [ABSTRACT FROM AUTHOR]

This paper presents tracking control method for wheeled mobile robots (WMRs) with state, sensor and control delays. The differential equations are obtained from the kinematic model of WMR with Pfaffian constraint. Thus, the state-space representations of WMR motion system and the target path system can be achieved. And the tracking error system with state, sensor and control delays is got. A nonlinear tracking control is designed with not only the state of future time but also that of past time. The exponential stability of the closed-loop system under the tracking control is proved. Since the control has the predictive states, it cannot be physically implemented. A high-gain observer (HGO) is constructed to solve this physical implement problem. Moreover, the exponential stability of the errors between the original states and the generated states from HGO is demonstrated. The simulation experiments verified the effectiveness, convenience and simplicity of the designed state-feedback control (SFC) and the output feedback control (OFC) via HGO, which illustrates that the target paths of a circle and a figure-of-8 can be successfully tracked by WMR under the proposed controllers by this paper. [ABSTRACT FROM AUTHOR]

Printed sensors have been explored for more than two decades and have now gained significant interest in real-world applications due to low cost, simple and scalable fabrication processes. These sensors must satisfy the requirement of long-term usage as wearable devices, especially for health monitoring and rehabilitation purposes. However, when such devices are continuously worn on the body or implanted within the body, they may cause unexpected risk to the patient's health. To avoid potential health risks, transition to 'green' strategies has already begun in the research, design and manufacturing of these sensors. This review is dedicated to offering a snapshot of current realization and future prospects of printed sensors through green strategies. The utilization of eco-friendly and cost-effective materials for sensor components and the adoption of various printing methods are summarized. The reusability and multi-detection capability of printed sensors that are within the scope of green analytical chemistry are discussed. [ABSTRACT FROM AUTHOR]

This paper presents a power efficient, low delay and rate adaptive dual chamber pacemaker (PLRDPM) using heart rate and accelerometer sensor. In recent years, number of modifications have been done in the pacemaker design. However, design of an implantable device on an open source is still challenging. Through this paper, we are proposing a "proof of concept" for the design of PLRDPM on FPGA for improving the vital parameters: delay and power consumption. The proposed PLRDPM comprises of accelerometer and heart rate sensors to measure physical activity's effect on heart rate of the bradycardia patients. A rate adaptive pacing algorithm has been designed using two sensor's data, to reduce the delay and power consumption. However, delay in the responses of various components in the circuitry produces an accumulative delay effect in any practical circuit. The delay and the power consumption for the proposed PLRDPM are found to be 2.82 ns and 9 mW, respectively. [ABSTRACT FROM AUTHOR]

This paper has proposed a multi-piezoelectric input synchronized switch harvesting on inductor (MI-SSHI) circuit. The MI-SSHI circuit is mainly composed of an extreme detector unit and synchronized switch harvesting on inductor (SSHI) units. The extreme detector unit generates real-time control signals. Since the principle of SSHI circuit, each voltage on piezoelectric element can be switched at different instant in a period. In this paper, two piezoelectric element inputs are selected as an example. The experimental result validates that the output power of the MI-SSHI circuit is improved by 11.67%, in comparison to the traditional S-SSHI circuit. [ABSTRACT FROM AUTHOR]

Since 1986, the first microcantilever applied in atomic force microscope, the device manufacturing technology, driving method and readout technology have improved significantly. In this paper, five readout technologies will be introduced in detail, and they are optical readout, piezoelectric readout, piezoresistive readout, capacitance readout and electron tunneling readout, respectively. Among them, the piezoresistive readout technology attracts a large number of researchers due to simple detection equipment, easy integration, and lower cost. In order to improve the detection accuracy of the piezoresistive microcantilever, a detection system based on FPGA is proposed in this paper. Output signal of the piezoresistive microcantilever array sensor for alpha-fetoprote (AFP) detection was researched. The detection accuracy of 0.05 Hz is achieved, the system stability is within 0.6 Hz, and it has a precise detection level for AFP with concentration of 50 pg/ml, which makes microcantilever has potential in early diagnosis and detection of liver cancer. [ABSTRACT FROM AUTHOR]

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Exploring the driving factors behind urban polycentricity is of paramount significance for advancing the implementation of urban polycentric strategies. In this, paper takes 41 cities in the China's Yangtze River Delta region are taken as the research objects, and the degree of urban polycentricity is measured using non-parametric and social network methods. Then, the geographic probe method is applied to reveal the driving factors of the spatial differentiation of urban polycentricity. The research results showed that (1) the distribution of hot and cold spots of the urban polycentricity index was roughly the same between 2006 and 2015, while and the distribution of hot and cold spots of the urban polycentricity index varied greatly between 2015 and 2020. (2) In 2010, the proportions of the secondary and industry tertiary industries and the topographic relief were the main driving factors of urban polycentricity. By 2020, the population size and topographic relief were the key drivers of urban polycentricity. [ABSTRACT FROM AUTHOR]

As a typical representative of water-soluble fullerene derivatives, fullerenols have been widely used in biomedicine, adsorption, and sensor detection. This paper has studied the structure and composition of commercial fullerenols, which indicate abundant hydrophilic groups exist on the surface of carbon cages to promote the adsorption of water molecules. It is found that the humidity sensor coated with fullerenols has a fast response (19s)/recovery time (12s) and low hysteresis (ΔH ≈ 2.68%RH) at the relative humidity level of 11–97%. The change mechanism of the impedance signal is due to the ions' formation caused by the adsorption of water molecules. Excellent repeatability and stability are still maintained after a long time of exposure in the air, which displays great application potential. [ABSTRACT FROM AUTHOR]

This paper considers model-based fault detection of large-scale (possibly rank-deficient) dynamic systems. Assuming only global (and not local) observability over a sensor network, we introduce a single time-scale networked estimator/observer. Sensors take local outputs/measurements of system states with partial observability and share their information (including estimation and/or output) over a communication network, and gain distributed observability. We define the conditions on the network structure ensuring distributed observability and stabilising the error dynamics. However, system outputs are prone to faults and uncertainties, which affect the state estimation of all sensors as a consequence of communicating (possibly) faulty data. From the cyber-physical-systems (CPS) perspective, such faults add bias to the data transferred from the physical layer (dynamic system) to the cyber layer (sensor network). In this work, we propose a localised fault detection and isolation (FDI) mechanism at sensors to secure distributed estimation. This protocol enables every sensor to locally identify the possible fault at the sensor measurement, and, via local detection and isolation, to prevent the spread of biased/faulty information over the network. This distributed isolation and localisation of fault follows from our partial observability assumption instead of full observability at every sensor. Then, other sensors can estimate/track the system by using observationally-equivalent output information to recover for possible loss of observability. In particular, we study rank-deficient systems as they are known to demand more information-sharing, and thus, are more vulnerable to the spread of possible faults over the network. One challenge is the detection of faults in the presence of system/output noise without making (simplifying and unrealistic) upper-bound assumptions on the noise support. We resolve this by adopting probabilistic threshold designs on the residuals. Further, we show that additive faults at rank-deficiency-related outputs affect the residuals at all sensors, a consequence that mandates more constraints on the (distributed) FDI strategy. We address this problem by constrained LMI design of the feedback gain matrix. Finally, we design q-redundant distributed estimators, resilient to isolation/removal of up to q number of faulty sensors, and further, we consider thresholding residual history over a sliding time-window, known as the stateful FDI. [ABSTRACT FROM AUTHOR]

In this paper, the problem of closed-loop intermittent sensor fault (ISF) detection is investigated for a class of linear stochastic time-delay systems with unknown disturbances. A modified unknown input observer (UIO) is proposed to eliminate the influence of delayed errors caused by the discrete-time proportional-integral controller and constant time delay. In order to detect the appearing time and disappearing time of the ISF, a truncated residual is designed by introducing a sliding-time window. Moreover, two hypothesis tests are utilised to set the ISF detection thresholds, and the detectability, false alarm rates as well as missing alarm rates of the ISF are analysed in the framework of statistical analysis. Finally, the effectiveness of the proposed method is validated via a simulation example of a simplified radial flight control system. [ABSTRACT FROM AUTHOR]

In a radar detection system, multiple pulse (MP) transmission is used to improve detection performance compared to the single pulse case by integrating the echoes of pulses at reception. In this paper, we derive closed-form expressions of the probability of false alarm PFA of the cell averaging-constant false alarm rate, greatest-of CFAR, and smallest-of CFAR detectors considering a homogeneous gamma distributed radar clutter applied to the MP case. Expressions are given by analytical formulas for a positive real shape parameter which correspond to a real situation and are validated by comparing them in terms of the detection threshold calculated values T, to the results obtained by means of Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

The International Mobile Telecommunications-2020 (IMT-2020) specifies the data rates for enhanced mobile broadband (eMBB) is approximately 10 Gb/s. Millimetre-wave (mmWave) has a vast spectrum and can be used with only slight authorisation, making it an ideal solution for eMBB. This paper proposes optimal detectors with low cost, low power consumption, and low complexity for mmWave massive multi-user multiple-input multiple-output (MU-MIMO) communication. The mmWave broadband communication faces many challenges in system implementation. One of the challenges of mmWave broadband systems is using the analog-to-digital converter (ADC) in the receiver. The ADC power consumption will significantly increase with the frequency bandwidth. The ADC power consumption will also considerably increase with the bit number used in the conversion simultaneously. The mmWave broadband communication also challenges the cost of transmitters, especially wideband linear amplifiers are costly. Hence, it is necessary to transmit a signal with a low peak-to-average power ratio (PAPR) to relax the linearity of the power amplifier. The radio-frequency (RF) port connects to two high-precision ADCs in conventional MIMO systems. Scaling such architectures to massive multiple-input multiple-output (MIMO) with hundreds or thousands of active antenna elements would lead to excessive-high power consumption and hardware costs. Hence, this paper proposes optimal detections for massive multi-user (MU) MIMO-GFDM communications with coarse quantisation. It achieves substantial cost and power savings and provides a high system capacity. The optimal detections for coarse quantisation in large-scale MU-MIMO-GFDM systems have minimal capability loss compared with the ideal case. There is no additional base-band processing complexity. The simulation results show that the SNR gap between the second mismatched quantiser and the precise quantiser is small. When the ratio of receiving and transmitting antennas is the same, the larger the number of antennas, the smaller the SNR difference between the second mismatch quantiser and the precise quantiser. [ABSTRACT FROM AUTHOR]

In this paper, we address the distributed resilient fusion filtering (DRFF) problem for a class of nonlinear multi-sensor networked systems (MSNSs) with random sensor delay (RSD) under round-robin protocol (RRP). The RSD is depicted by the Bernoulli random variable with known occurrence probability. In order to relieve the network congestion, the RRP that can deal with information overload issue of the transmission process from sensor to the estimator is utilised. The major objective of this paper is that the resilient fusion filter is designed for nonlinear MSNSs with RSD and RRP in the light of the inverse covariance intersection approach, where the local upper bound regarding the filtering error covariance is obtained and then minimised by suitably exploiting the local filter gain. Finally, a simulation example that can show the validity of the provided DRFF algorithm is presented. [ABSTRACT FROM AUTHOR]

In this paper, the set-membership filtering problem is investigated for a class of polytopic uncertain two-dimensional shift-varying systems with delays and sensor saturation. The measurement information is transmitted between the sensors and the filter through a shared communication network. To avoid data congestions, the Round-Robin (R-R) protocol is employed to regulate the data transmission order. This paper aims to design a robust set-membership filter such that the real system states are always contained in the state estimate ellipsoid in the presence of the state delays, the sensor saturation, the parameter uncertainties, the R-R protocol and the unknown-but-bounded external perturbations. By using the mathematical induction, sufficient condition for the existence of the desired robust set-membership filter is given in the form of recursive linear matrix inequalities, and a convex optimisation method is also proposed to determine the optimal state estimation ellipsoid in the trace sense. One numerical example is also given to illustrate effectiveness of the proposed filtering strategy. [ABSTRACT FROM AUTHOR]

In recent years, China has launched a number of Gaofen (GF) series earth observation satellites. It is crucial to understand the relationship between the data of the GF series of satellite sensors for the selection of sensor images for scientific research. Taking the same-day transit image pairs of three regions as the study data, this paper compares the consistency of the Top of Atmosphere (TOA) reflectance of GF-1 WFV4 and GF-6 WFV sensors by using the TOA mean comparison method, and discusses the differences in water body and vegetation extraction. The results indicate that the satellite signal intensity in different land cover types and areas differs significantly. In the bare soil-dominated region, GF-1 WFV4 has a larger signal strength than GF-6 WFV, while in the vegetation-dominated region, it turns out to be just the opposite. The difference between the two sensors is mainly related to the difference in the spectral response function and the radiometric resolution of the two satellites. In addition, the determination coefficient (R2) of the corresponding bands of the two sensors is all greater than 0.90, indicating that the two sensors have strong linear correlation and good complementarity. [ABSTRACT FROM AUTHOR]

Measuring the volume fraction of different types of fluids with two or three phases is so vital. Among all available methods, two of them, capacitance-based and gamma-ray attenuation, are so popular and widely used. Moreover, nowadays, AI which stands for Artificial Intelligence can be seen almost in all areas, and the measuring section is no exception. In this paper, the main goal is to predict the volume fraction of a three-phase homogeneous fluid which contains water, oil, and gas materials. To opt for an optimised method, a combination of capacitance-based sensors, gamma-ray attenuation sensor and Artificial Neural Networks (ANN) is utilised. To train the proposed metering system which is a MLP type, two inputs are considered. For the first input, the concave sensor is simulated in COMSOL Multiphysics software and different combinations of three phases (different volume fractions) are applied. Then through theoretical investigations of gamma-ray sensor, Barium-133 which radiates 0.356 MeV is used. This way, the second required input is generated. Finally, to implement a new and accurate metering system, a number of networks with different characteristics are run in the MATLAB software. The best structure had a Mean Absolute Error (MAE) equal to 0.33, 3.68 and 3.75 for the water, gas and oil phases, respectively. The accuracy of the presented metering system is illustrated by the received outcomes. The novelty of this study is proposing a new combined method that can measure a three-phase homogeneous fluid’s volume fractions containing water, gas and oil, precisely. [ABSTRACT FROM AUTHOR]

AbstractChirality represents a fundamental attribute within living systems and is a pervasive phenomenon in the natural world. The identification and analysis of chiral materials within natural environments and biological systems hold paramount importance in clinical, chemical, and biological sciences. Within chiral analysis, there is a burgeoning focus on developing chiral sensors exhibiting exceptional selectivity, sensitivity, and stability, marking it as a forefront area of research. In the past decade (2013–2023), approximately 1990 papers concerning the application of various chiral materials in chiral sensors have been published. Biological materials and nanomaterials have important applications in the development of chiral sensors, which accounting for 26.67% and 45.24% of the material-related applications in these sensors, respectively; moreover, the development of chiral nanomaterials is closely related to the development of portable and stable chiral sensors. Natural chiral materials, utilized as selective recognition units, are combined with carriers characterized by good physical and chemical properties through functionalization to form various functional chiral materials, which improve the recognition efficiency of chiral sensors. In this article, from the perspective of biological materials, polymer materials, nanomaterials, and other functional chiral materials, the applications of chiral sensors are summarized and the research prospects of chiral sensors are discussed. [ABSTRACT FROM AUTHOR]

Mode shapes are sensitive to the structural condition of bridges but a reasonable estimate of such changes require several accelerometers, which can be resource intensive. This paper obviates this problem through a novel structure health monitoring (SHM) approach for estimating modal parameters of bridges, including damage-induced changes of boundary conditions by using progressively re-deploying sensors along a monitored bridge. This concept of re-deployable sensors and subsequent use of a series of measurements allow extracting data from different bridge segments and also to get an indication of the condition of the bridge through frequency domain decomposition. Data from different segments are combined to estimate the global mode shape of the bridge and its gradient is observed to be indicative of support stiffness change. The concept is successfully tested through a full-scale field trial on a railway bridge in the Republic of Ireland, before and after the rehabilitation of its supports. The results are expected to guide future on-site measurement of damages due to flooding, scour, and other natural hazards, along with the effectiveness of intervention actions like repair and rehabilitation, providing a clear evidence base for practical value of SHM. [ABSTRACT FROM AUTHOR]

In this paper, an anemometric type flow meter has been designed and developed using a transistor as a flow sensor. The heat is dissipated from the surface of the p–n diode created by short circuiting the emitter and base terminal of the transistor CL100B causing the drop in the temperature with respect to the fluid velocity and it is utilized to measure the flow rate of the fluid across the pipeline section. Two identical sets of transistor acting like p–n diodes are used, the first diode senses the fluid velocity and produces an inconstant voltage and the other is in contact with the stagnated fluid produces a constant voltage. In this paper, the temperature effect is easily compensated by taking the difference in the output of diodes. The difference between the output voltages of the identical transducer only depends on the flow rate. The transducer design and its theoretical characteristic equation and graphs have been derived and discussed in this paper. The proposed transducer has a low cost with good linearity, accuracy, and repeatability. [ABSTRACT FROM AUTHOR]

Recognition of Indian Sign Language (ISL) could bridge the gap between deaf-mute people and society. Hand recognition is a key requirement for ISL recognition system. In this paper, the hand region is segmented from the depth image using the Microsoft Kinect Sensor in the cluttered environment. The depth image obtained is then used to implement supervised machine learning by extracting and training the features of images. Here, by comparing various methods, it is depicted that ORB (Oriented FAST and Rotated BRIEF) outruns others in terms of accuracy. ORB is invariant to scale, rotation, and lighting conditions. ORB is also fused with various classification techniques to gain the optimum result. The method is applied to images of ISL 0–9 and is also compared with some standard datasets. Tuning of the ORB with k-NN classification produces an average recognition accuracy of 93.26% with ISL dataset. [ABSTRACT FROM AUTHOR]

The advancement of ultra-hyperspectral imaging technology, exemplified by the AisaIBIS sensor, has enabled a leap from hyperspectral data (hundreds of bands) to ultra-hyperspectral data (thousands of bands). It provides immense potential for precise ground object recognition within intricate scenes. However, the complexities inherent to features of the ground objects, coupled with the copious redundant information within the ultra-hyperspectral data, pose substantial challenges for accurate object recognition. Therefore, this paper proposed a comprehensive framework to explore the optimal precise classification strategy of ultra-hyperspectral data in complex scenes (12 vegetation and non-vegetation classes). (a) Our investigation delves into the influence of diverse feature subsets and a range of machine learning classifiers on the precision of ground objects recognition. The proposed strategy is up to an overall accuracy of 88.44%, effectively avoiding the curse of dimension, and significantly enhancing the capability to recognize the complex ground objects. (b) Furthermore, based on the simulation of hyperspectral images with different spectral resolutions, we compared the classification results of ultra-hyperspectral data (0.11 nm) and the hyperspectral datasets (10 nm, 5 nm, and 1 nm) by machine learning methods. Compared with the hyperspectral datasets, ultra-hyperspectral data improved the classification accuracy by 5.30–6.38%. This substantiates the pronounced advantages of ultra-hyperspectral data in precision land cover classification. This study provides a valuable reference for the application of ultra-hyperspectral data in recognition of complex ground objects scenes, and urban accurate monitoring. [ABSTRACT FROM AUTHOR]

This paper investigates the neural network (NN) adaptive consensus output-feedback control problem for a class of nonlinear multi-agent systems (MASs) encountered sensor attacks. To overcome the impact of unknown sensor attacks, a NN estimation algorithm is adopted to estimate the unknown sensor attacks. Subsequently, a novel NN observer is established to estimate the states of encountered sensor attacks. Consequently, under the framework of backstepping control design, an adaptive NN consensus control method is proposed. By using the Lyapunov stability theory, the proposed consensus control method can not only ensure that all the signals of controlled MASs remain bounded, but also make all followers maintain consensus with the trajectory of the leader. Simulation results and comparative results illustrate the effectiveness of the proposed consensus control scheme. [ABSTRACT FROM AUTHOR]

Model predictive control (MPC) is considered one of the best non-linear control methods for controlling the modular multilevel converter (MMC) due to various advantages, such as no need for direct modelling, high dynamic response, and the ability to manage multiple control targets simultaneously. In this paper, a current closed-loop controller (CCLC) based on the current predictive strategy (CPS) is used to control the circulating and output currents in an MMC. A bilinear mathematical model of the MMC is derived and discretized to predict the states of the MMC for one step ahead. In addition, to reduce the practical costs and reduce the converter sensors, a sensor reduction algorithm has been used to reduce the number of voltage sensors and increase the reliability of the system. The proposed method is implemented in a single-phase MMC with four sub-modules (SMs) in each arm. The accuracy and performance of the proposed method are evaluated with simulation and experimental results. [ABSTRACT FROM AUTHOR]

Interstrip capacitance plays a crucial role on the detector electronic noise performance at the readout electrode of the irradiated detectors in the harsh radiation environment of the high luminosity Large Hadron Collider experiments. The major challenge is to optimize the design of the detector to get the low interstrip capacitance in the real 'mixed' irradiation environment of the experiment. A few of experimental studies have been performed within CERN RDD0 collaboration on the n-MCz Si detectors to extract the microscopic parameters for the surface and bulk damage effects especially by mixed irradiations in the detectors. The results on the microscopic parameters are fed into ATLAS TCAD commercial simulation program to compare the experimental data and simulation result. A very good agreement has been recorded between the data and simulation result. In this paper, the microscopic model parameters are used to investigate the effects of mixed irradiation up to a fluence of 8.82× 1014 neq./cm2 on the interstrip capacitance in n-MCz 〈100〉 silicon microstrip detectors. The results are discussed in detail using electric field distribution, electron concentration profile in the irradiated detectors for the different metal overhang width, and an optimized p+n-MCz Si microstrip design is proposed for the future collider experiment. [ABSTRACT FROM AUTHOR]

A slot microring resonator acoustic sensor (MRAS) using the PDMS package was proposed to achieve ultra-high sensitivity acoustic detection. The acoustic detection principle of the sensor is analyzed theoretically, the structural parameters are optimized and the performance of the sensor is verified by simulation. The simulation results show that the proposed slot MRAS has a high-quality factor of 1.49 × 106, the sensitivity of the sensor by intensity detection method is up to 3872 mV/kPa, and the 3 dB bandwidth is 210 MHz. The sensor designed in this paper has the advantages of ultra-high sensitivity and wide bandwidth range, which has important value in the field of acoustic detection. [ABSTRACT FROM AUTHOR]