Sensors, Volume 16, Issue 4 (April 2016) – 171 articles

This study analyzes muscle activity, recorded in an eight-channel electromyographic (EMG) signal stream, during the golf swing using a 7-iron club and exploits information extracted from EMG dynamics to predict the success of the resulting shot. Muscles of the arm and shoulder on both the left and right sides, namely flexor carpi radialis, extensor digitorum communis, rhomboideus and trapezius, are considered for 15 golf players (∼5 shots each). The method using Gaussian filtering is outlined for EMG onset time estimation in each channel and activation sequence profiling. Shots of each player revealed a persistent pattern of muscle activation. Profiles were plotted and insights with respect to player effectiveness were provided. Inspection of EMG dynamics revealed a pair of highest peaks in each channel as the hallmark of golf swing, and a custom application of peak detection for automatic extraction of swing segment was introduced. Various EMG features, encompassing 22 feature sets, were constructed. Feature sets were used individually and also in decision-level fusion for the prediction of shot effectiveness. The prediction of the target attribute, such as club head speed or ball carry distance, was investigated using random forest as the learner in detection and regression tasks. Detection evaluates the personal effectiveness of a shot with respect to the player-specific average, whereas regression estimates the value of target attribute, using EMG features as predictors. Fusion after decision optimization provided the best results: the equal error rate in detection was 24.3% for the speed and 31.7% for the distance; the mean absolute percentage error in regression was 3.2% for the speed and 6.4% for the distance. Proposed EMG feature sets were found to be useful, especially when used in combination. Rankings of feature sets indicated statistics for muscle activity in both the left and right body sides, correlation-based analysis of EMG dynamics and features derived from the properties of two highest peaks as important predictors of personal shot effectiveness. Activation sequence profiles helped in analyzing muscle orchestration during golf shot, exposing a specific avalanche pattern, but data from more players are needed for stronger conclusions. Results demonstrate that information arising from an EMG signal stream is useful for predicting golf shot success, in terms of club head speed and ball carry distance, with acceptable accuracy. Surface EMG data, collected with a goal to automatically evaluate golf player’s performance, enables wearable computing in the field of ambient intelligence and has potential to enhance exercising of a long carry distance drive. Full article

In this paper, we analyze the applicability of color-space-based, color-independent visual-MIMO for V2X. We aim to achieve a visual-MIMO scheme that can maintain the original color and brightness while performing seamless communication. We consider two scenarios of GCM based visual-MIMO for V2X. One is a multipath transmission using visual-MIMO networking and the other is multi-node V2X communication. In the scenario of multipath transmission, we analyze the channel capacity numerically and we illustrate the significance of networking information such as distance, reference color (symbol), and multiplexing-diversity mode transitions. In addition, in the V2X scenario of multiple access, we may achieve the simultaneous multiple access communication without node interferences by dividing the communication area using image processing. Finally, through numerical simulation, we show the superior SER performance of the visual-MIMO scheme compared with LED-PD communication and show the numerical result of the GCM based visual-MIMO channel capacity versus distance. Full article

In this paper, we propose a new unsupervised method to automatically characterize and detect events in multichannel signals. This method is used to identify artifacts in electroencephalogram (EEG) recordings of brain activity. The proposed algorithm has been evaluated and compared with a supervised method. To this end an example of the performance of the algorithm to detect artifacts is shown. The results show that although both methods obtain similar classification, the proposed method allows detecting events without training data and can also be applied in signals whose events are unknown a priori. Furthermore, the proposed method provides an optimal window whereby an optimal detection and characterization of events is found. The detection of events can be applied in real-time. Full article

Diabetic individuals need to tightly control their blood glucose concentration. Several methods have been developed for this purpose, such as the finger-prick or continuous glucose monitoring systems (CGMs). However, these methods present the disadvantage of being invasive. Moreover, CGMs have limited accuracy, notably to detect hypoglycemia. It is also known that physical exercise, and even daily activity, disrupt glucose dynamics and can generate problems with blood glucose regulation during and after exercise. In order to deal with these challenges, devices for monitoring patients’ physical activity are currently under development. This review focuses on non-invasive sensors using physiological parameters related to physical exercise that were used to improve glucose monitoring in type 1 diabetes (T1DM) patients. These devices are promising for diabetes management. Indeed they permit to estimate glucose concentration either based solely on physical activity parameters or in conjunction with CGM or non-invasive CGM (NI-CGM) systems. In these last cases, the vital signals are used to modulate glucose estimations provided by the CGM and NI-CGM devices. Finally, this review indicates possible limitations of these new biosensors and outlines directions for future technologic developments. Full article

Storm-based stream processing is widely used for real-time large-scale distributed processing. Knowing the run-time status and ensuring performance is critical to providing expected dependability for some applications, e.g., continuous video processing for security surveillance. The existing scheduling strategies’ granularity is too coarse to have good performance, and mainly considers network resources without computing resources while scheduling. In this paper, we propose Healthcare4Storm, a framework that finds Storm insights based on Storm metrics to gain knowledge from the health status of an application, finally ending up with smart scheduling decisions. It takes into account both network and computing resources and conducts scheduling at a fine-grained level using tuples instead of topologies. The comprehensive evaluation shows that the proposed framework has good performance and can improve the dependability of the Storm-based applications. Full article

This paper presents HybridPLAY, a novel technology composed of a sensor and mobile-based video games that transforms urban playgrounds into game scenarios. With this technology we aim to stimulate physical activity and playful learning by creating an entertaining environment in which users can actively participate and collaborate. HybridPLAY is different from other existing technologies that enhance playgrounds, as it is not integrated in them but can be attached to the different elements of the playgrounds, making its use more ubiquitous (i.e., not restricted to the playgrounds). HybridPLAY was born in 2007 as an artistic concept, and evolved after different phases of research and testing by almost 2000 users around the world (in workshops, artistic events, conferences, etc.). Here, we present the temporal evolution of HybridPLAY with the different versions of the sensors and the video games, and a detailed technical description of the sensors and the way interactions are produced. We also present the outcomes after the evaluation by users at different events and workshops. We believe that HybridPLAY has great potential to contribute to increased physical activity in kids, and also to improve the learning process and monitoring at school centres by letting users create the content of the apps, leading to new narratives and fostering creativity. Full article

Leaf area index (LAI) and plant area index (PAI) are common and important biophysical parameters used to estimate agronomical variables such as canopy growth, light interception and water requirements of plants and trees. LAI can be either measured directly using destructive methods or indirectly using dedicated and expensive instrumentation, both of which require a high level of know-how to operate equipment, handle data and interpret results. Recently, a novel smartphone and tablet PC application, VitiCanopy, has been developed by a group of researchers from the University of Adelaide and the University of Melbourne, to estimate grapevine canopy size (LAI and PAI), canopy porosity, canopy cover and clumping index. VitiCanopy uses the front in-built camera and GPS capabilities of smartphones and tablet PCs to automatically implement image analysis algorithms on upward-looking digital images of canopies and calculates relevant canopy architecture parameters. Results from the use of VitiCanopy on grapevines correlated well with traditional methods to measure/estimate LAI and PAI. Like other indirect methods, VitiCanopy does not distinguish between leaf and non-leaf material but it was demonstrated that the non-leaf material could be extracted from the results, if needed, to increase accuracy. VitiCanopy is an accurate, user-friendly and free alternative to current techniques used by scientists and viticultural practitioners to assess the dynamics of LAI, PAI and canopy architecture in vineyards, and has the potential to be adapted for use on other plants. Full article

Secure data aggregation (SDA) schemes are widely used in distributed applications, such as mobile sensor networks, to reduce communication cost, prolong the network life cycle and provide security. However, most SDA are only suited for a single type of statistics (i.e., summation-based or comparison-based statistics) and are not applicable to obtaining multiple statistic results. Most SDA are also inefficient for dynamic networks. This paper presents multi-functional secure data aggregation (MFSDA), in which the mapping step and coding step are introduced to provide value-preserving and order-preserving and, later, to enable arbitrary statistics support in the same query. MFSDA is suited for dynamic networks because these active nodes can be counted directly from aggregation data. The proposed scheme is tolerant to many types of attacks. The network load of the proposed scheme is balanced, and no significant bottleneck exists. The MFSDA includes two versions: MFSDA-I and MFSDA-II. The first one can obtain accurate results, while the second one is a more generalized version that can significantly reduce network traffic at the expense of less accuracy loss. Full article

Nanozyme-based chemical sensing is a rapidly emerging field of research. Herein, a simple colorimetric assay for the detection of hydrogen peroxide and glucose based on the peroxidase-like activity of V₂O₅ nanozymes has been established. In this assay, the effects of pH, substrate, nanozyme concentrations and buffer solution have been investigated. It was found that compared with 3,3′,5,5′-tetramethylbenzidine (TMB), the enzyme substrate o-phenylenediamine (OPD) seriously interfered with the H₂O₂ detection. Under the optimal reaction conditions, the resulting sensor displayed a good response to H₂O₂ with a linear range of 1 to 500 μM, and a detection limit of 1 μM at a signal-to-noise ratio of 3. A linear correlation was established between absorbance intensity and concentration of glucose from 10 to 2000 μM, with a detection limit of 10 μM. The current work presents a simple, cheap, more convenient, sensitive, and easy handling colorimetric assay. Full article

Guided Wave Testing (GWT) using novel Electromagnetic Acoustic Transducers (EMATs) is proposed for the inspection of large structures operating at high temperatures. To date, high temperature EMATs have been developed only for thickness measurements and they are not suitable for GWT. A pair of water-cooled EMATs capable of exciting and receiving Shear Horizontal (SH₀) waves for GWT with optimal high temperature properties (up to 500 °C) has been developed. Thermal and Computational Fluid Dynamic (CFD) simulations of the EMAT design have been performed and experimentally validated. The optimal thermal EMAT design, material selection and operating conditions were calculated. The EMAT was successfully tested regarding its thermal and GWT performance from ambient temperature to 500 °C. Full article

This study assessed changes in electrical impedance myography (EIM) at different levels of isometric muscle contraction as well as during exhaustive exercise at 60% maximum voluntary contraction (MVC) until task failure. The EIM was performed on the biceps brachii muscle of 19 healthy subjects. The results showed that there was a significant difference between the muscle resistance (R) measured during the isometric contraction and when the muscle was completely relaxed. Post hoc analysis shows that the resistance increased at higher contractions (both 60% MVC and MVC), however, there were no significant changes in muscle reactance (X) during the isometric contractions. The resistance also changed during different stages of the fatigue task and there were significant decreases from the beginning of the contraction to task failure as well as between task failure and post fatigue rest. Although our results demonstrated an increase in resistance during isometric contraction, the changes were within 10% of the baseline value. These changes might be related to the modest alterations in muscle architecture during a contraction. The decrease in resistance seen with muscle fatigue may be explained by an accumulation of metabolites in the muscle tissue. Full article

In urban areas or space-constrained environments with obstacles, vehicle localization using Global Navigation Satellite System (GNSS) data is hindered by Non-Line Of Sight (NLOS) and multipath receptions. These phenomena induce faulty data that disrupt the precise localization of the GNSS receiver. In this study, we detect the outliers among the observations, Pseudo-Range (PR) and/or Doppler measurements, and we evaluate how discarding them improves the localization. We specify a contrario modeling for GNSS raw data to derive an algorithm that partitions the dataset between inliers and outliers. Then, only the inlier data are considered in the localization process performed either through a classical Particle Filter (PF) or a Rao-Blackwellization (RB) approach. Both localization algorithms exclusively use GNSS data, but they differ by the way Doppler measurements are processed. An experiment has been performed with a GPS receiver aboard a vehicle. Results show that the proposed algorithms are able to detect the ‘outliers’ in the raw data while being robust to non-Gaussian noise and to intermittent satellite blockage. We compare the performance results achieved either estimating only PR outliers or estimating both PR and Doppler outliers. The best localization is achieved using the RB approach coupled with PR-Doppler outlier estimation. Full article

A practical compact solid-state terahertz imaging system is presented. Various beam guiding architectures were explored and hardware performance assessed to improve its compactness, robustness, multi-functionality and simplicity of operation. The system performance in terms of image resolution, signal-to-noise ratio, the electronic signal modulation versus optical chopper, is evaluated and discussed. The system can be conveniently switched between transmission and reflection mode according to the application. A range of imaging application scenarios was explored and images of high visual quality were obtained in both transmission and reflection mode. Full article

The aim of this study was to design a navigation system composed of a human-controlled leader vehicle and a follower vehicle. The follower vehicle automatically tracks the leader vehicle. With such a system, a human driver can control two vehicles efficiently in agricultural operations. The tracking system was developed for the leader and the follower vehicle, and control of the follower was performed using a camera vision system. A stable and accurate monocular vision-based sensing system was designed, consisting of a camera and rectangular markers. Noise in the data acquisition was reduced by using the least-squares method. A feedback control algorithm was used to allow the follower vehicle to track the trajectory of the leader vehicle. A proportional–integral–derivative (PID) controller was introduced to maintain the required distance between the leader and the follower vehicle. Field experiments were conducted to evaluate the sensing and tracking performances of the leader-follower system while the leader vehicle was driven at an average speed of 0.3 m/s. In the case of linear trajectory tracking, the RMS errors were 6.5 cm, 8.9 cm and 16.4 cm for straight, turning and zigzag paths, respectively. Again, for parallel trajectory tracking, the root mean square (RMS) errors were found to be 7.1 cm, 14.6 cm and 14.0 cm for straight, turning and zigzag paths, respectively. The navigation performances indicated that the autonomous follower vehicle was able to follow the leader vehicle, and the tracking accuracy was found to be satisfactory. Therefore, the developed leader-follower system can be implemented for the harvesting of grains, using a combine as the leader and an unloader as the autonomous follower vehicle. Full article

Device-free localization (DFL) based on wireless sensor networks (WSNs) is expected to detect and locate a person without the need for any wireless devices. Radio tomographic imaging (RTI) has attracted wide attention from researchers as an emerging important technology in WSNs. However, there is much room for improvement in localization estimation accuracy. In this paper, we propose a geometry-based elliptical model and adopt the orthogonal matching pursuit (OMP) algorithm. The new elliptical model uses not only line-of-sight information, but also non-line-of-sight information, which divides one ellipse into several areas with different weights. Meanwhile the OMP, which can eliminate extra bright spots in image reconstruction, is used to derive an image estimator. The experimental results demonstrate that the proposed algorithm could improve the accuracy of positioning by up to 23.8% for one person and 33.3% for two persons over some state-of-the-art RTI methods. Full article

In order to measure the impedance variation process in electrolyte solutions, a method of triangular waveform voltage excitation is investigated together with principal component analysis (PCA). Using triangular waveform voltage as the excitation signal, the response current during one duty cycle is sampled to construct a measurement vector. The measurement matrix is then constructed by the measurement vectors obtained from different measurements. After being processed by PCA, the changing information of solution impedance is contained in the loading vectors while the response current and noise information is contained in the score vectors. The measurement results of impedance variation by the proposed signal processing method are independent of the equivalent impedance model. The noise-induced problems encountered during equivalent impedance calculation are therefore avoided, and the real-time variation information of noise in the electrode-electrolyte interface can be extracted at the same time. Planar-interdigitated electrodes are experimentally tested for monitoring the KCl concentration variation process. Experimental results indicate that the measured impedance variation curve reflects the changing process of solution conductivity, and the amplitude distribution of the noise during one duty cycle can be utilized to analyze the contact conditions of the electrode and electrolyte interface. Full article

Recently, commercial unmanned aerial systems (UAS) have gained popularity. However, these UAS are potential threats to people in terms of safety in public places, such as public parks or stadiums. To reduce such threats, we consider a design, modeling, and evaluation of a cost-efficient sensor system that detects and tracks small UAS. In this research, we focus on discovering the best sensor deployments by simulating different types and numbers of sensors in a designated area, which provide reasonable detection rates at low costs. Also, the system should cover the crowded areas more thoroughly than vacant areas to reduce direct threats to people underneath. This research study utilized the Agent-Based Modeling (ABM) technique to model a system consisting of independent and heterogeneous agents that interact with each other. Our previous work presented the ability to apply ABM to analyze the sensor configurations with two types of radars in terms of cost-efficiency. The results from the ABM simulation provide a list of candidate configurations and deployments that can be referred to for applications in the real world environment. Full article

Food pathogens are the cause of foodborne epidemics, therefore there is a need to detect the pathogens in food productions rapidly. A pre-enrichment culture followed by selective agar plating are standard detection methods. Molecular methods such as qPCR have provided a first rapid protocol for detection of pathogens within 24 h of enrichment culture. Biosensors also may provide a rapid tool to individuate a source of Salmonella contamination at early times of pre-enrichment culture. Forty mL of Salmonella spp. enrichment culture were processed by immunoseparation using the Pathatrix, as in AFNOR validated qPCR protocols. The Salmonella biosensor combined with immunoseparation showed a limit of detection of 100 bacteria/40 mL, with a 400 fold increase to previous results. qPCR analysis requires processing of bead-bound bacteria with lysis buffer and DNA clean up, with a limit of detection of 2 cfu/50 μL. Finally, a protein chip was developed and tested in screening and identification of 5 common pathogen species, Salmonella spp., E. coli, S. aureus, Campylobacter spp. and Listeria spp. The protein chip, with high specificity in species identification, is proposed to be integrated into a Lab-on-Chip system, for rapid and reproducible screening of Salmonella spp. and other pathogen species contaminating food productions. Full article

Underwater shock waves (SWs) generated by underwater electrical wire explosions (UEWEs) have been widely studied and applied. Precise measurement of this kind of SWs is important, but very difficult to accomplish due to their high peak pressure, steep rising edge and very short pulse width (on the order of tens of μs). This paper aims to analyze the signals obtained by two kinds of commercial piezoelectric pressure probes, and reconstruct the correct pressure waveform from the distorted one measured by the pressure probes. It is found that both PCB138 and Müller-plate probes can be used to measure the relative SW pressure value because of their good uniformities and linearities, but none of them can obtain precise SW waveforms. In order to approach to the real SW signal better, we propose a new multi-exponential pressure waveform model, which has considered the faster pressure decay at the early stage and the slower pressure decay in longer times. Based on this model and the energy conservation law, the pressure waveform obtained by the PCB138 probe has been reconstructed, and the reconstruction accuracy has been verified by the signals obtained by the Müller-plate probe. Reconstruction results show that the measured SW peak pressures are smaller than the real signal. The waveform reconstruction method is both reasonable and reliable. Full article

The development of image sensor and optics enables the application of vision-based techniques to the non-contact dynamic vibration analysis of large-scale structures. As an emerging technology, a vision-based approach allows for remote measuring and does not bring any additional mass to the measuring object compared with traditional contact measurements. In this study, a high-speed vision-based sensor system is developed to extract structure vibration signals in real time. A fast motion extraction algorithm is required for this system because the maximum sampling frequency of the charge-coupled device (CCD) sensor can reach up to 1000 Hz. Two efficient subpixel level motion extraction algorithms, namely the modified Taylor approximation refinement algorithm and the localization refinement algorithm, are integrated into the proposed vision sensor. Quantitative analysis shows that both of the two modified algorithms are at least five times faster than conventional upsampled cross-correlation approaches and achieve satisfactory error performance. The practicability of the developed sensor is evaluated by an experiment in a laboratory environment and a field test. Experimental results indicate that the developed high-speed vision-based sensor system can extract accurate dynamic structure vibration signals by tracking either artificial targets or natural features. Full article

Body area sensor networks (BANs) utilize wireless communicating sensor nodes attached to a human body for convenience, safety, and health applications. Physiological characteristics of the body, such as the heart rate or Electrocardiogram (ECG) signals, are promising means to simplify the setup process and to improve security of BANs. This paper describes the design and implementation steps required to realize an ECG-based authentication protocol to identify sensor nodes attached to the same human body. Therefore, the first part of the paper addresses the design of a body-area sensor system, including the hardware setup, analogue and digital signal processing, and required ECG feature detection techniques. A model-based design flow is applied, and strengths and limitations of each design step are discussed. Real-world measured data originating from the implemented sensor system are then used to set up and parametrize a novel physiological authentication protocol for BANs. The authentication protocol utilizes statistical properties of expected and detected deviations to limit the number of false positive and false negative authentication attempts. The result of the described holistic design effort is the first practical implementation of biometric authentication in BANs that reflects timing and data uncertainties in the physical and cyber parts of the system. Full article

Excessive fuel assembly vibrations in nuclear reactor cores should be avoided in order not to compromise the lifetime of the assembly and in order to prevent the occurrence of safety hazards. This issue is particularly relevant to new reactor designs that use liquid metal coolants, such as, for example, a molten lead-bismuth eutectic. The flow of molten heavy metal around and through the fuel assembly may cause the latter to vibrate and hence suffer degradation as a result of, for example, fretting wear or mechanical fatigue. In this paper, we demonstrate the use of optical fiber sensors to measure the fuel assembly vibration in a lead-bismuth eutectic cooled installation which can be used as input to assess vibration-related safety hazards. We show that the vibration characteristics of the fuel pins in the fuel assembly can be experimentally determined with minimal intrusiveness and with high precision owing to the small dimensions and properties of the sensors. In particular, we were able to record local strain level differences of about 0.2 μϵ allowing us to reliably estimate the vibration amplitudes and modal parameters of the fuel assembly based on optical fiber sensor readings during different stages of the operation of the facility, including the onset of the coolant circulation and steady-state operation. Full article

Magnetization of large Nd-Fe-B sintered permanent magnets is still challenging. This type of permanent magnet is electrically conductive, so impulse magnetization causes a flow of eddy currents which prevent magnetization of the whole volume of the magnet. The paper deals with the impulse magnetization of sintered Nd-Fe-B permanent magnets and shows a method for the determination of suitable parameters for the supply system. The necessary magnetic field strength for magnetization of the magnet to saturation was determined. The optimal magnetizing fixture supply voltage for magnetization to saturation was determined from simulations in PSpice software, finite element analyses in Maxwell 15 and measurements. Measurements of magnetic induction on the surface of the Nd-Fe-B magnet are also presented to ensure that a magnet with 70 mm diameter and 20 mm in height is fully saturated. Full article

During the night or in poorly lit areas, thermal cameras are a better choice instead of normal cameras for security surveillance because they do not rely on illumination. A thermal camera is able to detect a person within its view, but identification from only thermal information is not an easy task. The purpose of this paper is to reconstruct the face image of a person from the thermal spectrum to the visible spectrum. After the reconstruction, further image processing can be employed, including identification/recognition. Concretely, we propose a two-step thermal-to-visible-spectrum reconstruction method based on Canonical Correlation Analysis (CCA). The reconstruction is done by utilizing the relationship between images in both thermal infrared and visible spectra obtained by CCA. The whole image is processed in the first step while the second step processes patches in an image. Results show that the proposed method gives satisfying results with the two-step approach and outperforms comparative methods in both quality and recognition evaluations. Full article

Pipeline inspection gauges (pigs) have been used for many years to perform various maintenance operations in oil and gas pipelines. Different pipeline parameters can be inspected during the pig journey. Although pigs use many sensors to detect the required pipeline parameters, matching these data with the corresponding pipeline location is considered a very important parameter. High-end, tactical-grade inertial measurement units (IMUs) are used in pigging applications to locate the detected problems of pipeline using other sensors, and to reconstruct the trajectories of the pig. These IMUs are accurate; however, their high cost and large sizes limit their use in small diameter pipelines (8″ or less). This paper describes a new methodology for the use of MEMS-based IMUs using an extended Kalman filter (EKF) and the pipeline junctions to increase the position parameters’ accuracy and to reduce the total RMS errors even during the unavailability of above ground markers (AGMs). The results of this new proposed method using a micro-electro-mechanical systems (MEMS)-based IMU revealed that the position RMS errors were reduced by approximately 85% compared to the standard EKF solution. Therefore, this approach will enable the mapping of small diameter pipelines, which was not possible before. Full article

This paper studies the remote Kalman filtering problem for a distributed system setting with multiple sensors that are located at different physical locations. Each sensor encapsulates its own measurement data into one single packet and transmits the packet to the remote filter via a lossy distinct channel. For each communication channel, a time-homogeneous Markov chain is used to model the normal operating condition of packet delivery and losses. Based on the Markov model, a necessary and sufficient condition is obtained, which can guarantee the stability of the mean estimation error covariance. Especially, the stability condition is explicitly expressed as a simple inequality whose parameters are the spectral radius of the system state matrix and transition probabilities of the Markov chains. In contrast to the existing related results, our method imposes less restrictive conditions on systems. Finally, the results are illustrated by simulation examples. Full article

This paper compares three different methods capable of estimating the deflection of the vertical (DoV): one is based on the joint use of high precision spirit leveling and Global Navigation Satellite Systems (GNSS), a second uses astro-geodetic measurements and the third gravimetric geoid models. The working data sets refer to the geodetic International Terrestrial Reference Frame (ITRF) co-location sites of Medicina (Northern, Italy) and Noto (Sicily), these latter being excellent test beds for our investigations. The measurements were planned and realized to estimate the DoV with a level of precision comparable to the angular accuracy achievable in high precision network measured by modern high-end total stations. The three methods are in excellent agreement, with an operational supremacy of the astro-geodetic method, being faster and more precise than the others. The method that combines leveling and GNSS has slightly larger standard deviations; although well within the 1 arcsec level, which was assumed as threshold. Finally, the geoid model based method, whose 2.5 arcsec standard deviations exceed this threshold, is also statistically consistent with the others and should be used to determine the DoV components where local ad hoc measurements are lacking. Full article

Wheels are very important for the safety of a train. The diameter of the wheel is a significant parameter that needs regular inspection. Traditional methods only use the contact points of the wheel tread to fit the rolling round. However, the wheel tread is easily influenced by peeling or scraping. Meanwhile, the circle fitting algorithm is sensitive to noise when only three points are used. This paper proposes a dynamic measurement method based on structured-light vision. The axle of the wheelset and the tread are both employed. The center of the rolling round is determined by the axle rather than the tread only. Then, the diameter is calculated using the center and the contact points together. Simulations are performed to help design the layout of the sensors, and the influences of different noise sources are also analyzed. Static and field experiments are both performed, and the results show it to be quite stable and accurate. Full article

The research on intelligent bioelectrocatalysis based on stimuli-responsive materials or interfaces is of great significance for biosensors and other bioelectronic devices. In the present work, lectin protein concanavalin A (Con A) and glycoenzyme glucose oxidase (GOD) were assembled into {Con A/GOD}_n layer-by-layer (LbL) films by taking advantage of the biospecific lectin-glycoenzyme affinity between them. These film electrodes possess stimuli-responsive properties toward electroactive probes such as ferrocenedicarboxylic acid (Fc(COOH)₂) by modulating the surrounding pH. The CV peak currents of Fc(COOH)₂ were quite large at pH 4.0 but significantly suppressed at pH 8.0, demonstrating reversible stimuli-responsive on-off behavior. The mechanism of stimuli-responsive property of the films was explored by comparative experiments and attributed to the different electrostatic interaction between the films and the probes at different pH. This stimuli-responsive films could be used to realize active/inactive electrocatalytic oxidation of glucose by GOD in the films and mediated by Fc(COOH)₂ in solution, which may establish a foundation for fabricating novel stimuli-responsive electrochemical biosensors based on bioelectrocatalysis with immobilized enzymes. Full article

The effect of the sensitive area of the two-port resonator configuration on the mass sensitivity of a Rayleigh surface acoustic wave (R-SAW) sensor was investigated theoretically, and verified in experiments. A theoretical model utilizing a 3-dimensional finite element method (FEM) approach was established to extract the coupling-of-modes (COM) parameters in the absence and presence of mass loading covering the electrode structures. The COM model was used to simulate the frequency response of an R-SAW resonator by a P-matrix cascading technique. Cascading the P-matrixes of unloaded areas with mass loaded areas, the sensitivity for different sensitive areas was obtained by analyzing the frequency shift. The performance of the sensitivity analysis was confirmed by the measured responses from the silicon dioxide (SiO₂) deposited on different sensitive areas of R-SAW resonators. It is shown that the mass sensitivity varies strongly for different sensitive areas, and the optimal sensitive area lies towards the center of the device. Full article