ALBERT

Description: Bile acid diarrhoea (BAD) is a common disease that requires expensive imaging to diagnose. We have tested the efficacy of a new method to identify BAD, based on the detection of differences in volatile organic compounds (VOC) in urine headspace of BAD vs. ulcerative colitis and healthy controls. A total of 110 patients were recruited; 23 with BAD, 42 with ulcerative colitis (UC) and 45 controls. Patients with BAD also received standard imaging (Se75HCAT) for confirmation. Urine samples were collected and the headspace analysed using an AlphaMOS Fox 4000 electronic nose in combination with an Owlstone Lonestar Field Asymmetric Ion Mobility Spectrometer (FAIMS). A subset was also tested by gas chromatography, mass spectrometry (GCMS). Linear Discriminant Analysis (LDA) was used to explore both the electronic nose and FAIMS data. LDA showed statistical differences between the groups, with reclassification success rates (using an n-1 approach) at typically 83%. GCMS experiments confirmed these results and showed that patients with BAD had two chemical compounds, 2-propanol and acetamide, that were either not present or were in much reduced quantities in the ulcerative colitis and control samples. We believe that this work may lead to a new tool to diagnose BAD, which is cheaper, quicker and easier that current methods.

Description: This paper is a theoretical analysis of mirror tilt in a Michelson interferometer and its effect on the radiant flux over the active area of a rectangular photodetector or image sensor pixel. It is relevant to sensor applications using homodyne interferometry where these opto-electronic devices are employed for partial fringe counting. Formulas are derived for radiant flux across the detector for variable location within the fringe pattern and with varying wave front angle. The results indicate that the flux is a damped sine function of the wave front angle, with a decay constant of the ratio of wavelength to detector width. The modulation amplitude of the dynamic fringe pattern reduces to zero at wave front angles that are an integer multiple of this ratio and the results show that the polarity of the radiant flux changes exclusively at these multiples. Varying tilt angle causes radiant flux oscillations under an envelope curve, the frequency of which is dependent on the location of the detector with the fringe pattern. It is also shown that a fringe count of zero can be obtained for specific photodetector locations and wave front angles where the combined effect of fringe contraction and fringe tilt can have equal and opposite effects. Fringe tilt as a result of a wave front angle of 0.05° can introduce a phase measurement difference of 16° between a photodetector/pixel located 20 mm and one located 100 mm from the optical origin.

Description: In this study, a miniaturized high fundamental frequency quartz crystal microbalance (QCM) is fabricated for sensor applications using a wet etching technique. The vibration area is reduced in the fabrication of the high frequency QCM with an inverted mesa structure. To reduce the complexity of the side wall profile that results from anisotropic quartz etching, a rectangular vibration area is used instead of the conventional circular structure. QCMs with high Q values exceeding 25,000 at 47 MHz, 27,000 at 60 MHz, 24,000 at 73 MHz and 25,000 at 84 MHz are fabricated on 4 × 4 mm2 chips with small vibration areas of 1.2 × 1.4 mm2. A PMMA-based flow cell is designed and manufactured to characterize the behavior of the fabricated QCM chip in a liquid. Q values as high as 1,006 at 47 MHz, 904 at 62 MHz, 867 at 71 MHz and 747 at 84 MHz are obtained when one side of the chip is exposed to pure water. These results show that fabricated QCM chips can be used for bio- and chemical sensor applications in liquids.

Description: Finger vein recognition is a promising biometric recognition technology, which verifies identities via the vein patterns in the fingers. Binary pattern based methods were thoroughly studied in order to cope with the difficulties of extracting the blood vessel network. However, current binary pattern based finger vein matching methods treat every bit of feature codes derived from different image of various individuals as equally important and assign the same weight value to them. In this paper, we propose a finger vein recognition method based on personalized weight maps (PWMs). The different bits have different weight values according to their stabilities in a certain number of training samples from an individual. Firstly we present the concept of PWM, and then propose the finger vein recognition framework, which mainly consists of preprocessing, feature extraction, and matching. Finally, we design extensive experiments to evaluate the effectiveness of our proposal. Experimental results show that PWM achieves not only better performance, but also high robustness and reliability. In addition, PWM can be used as a general framework for binary pattern based recognition.

Description: The aim of this work is to study the sensing behavior of Sr-doped hematite for soil water content measurement. The material was prepared by solid state reaction from commercial hematite and strontium carbonate heat treated at 900 °C. X-Ray diffraction, scanning electron microscopy and mercury intrusion porosimetry were used for microstructural characterization of the synthesized powder. Sensors were then prepared by uniaxially pressing and by screen-printing, on an alumina substrate, the prepared powder and subsequent firing in the 800–1,000 °C range. These sensors were first tested in a laboratory apparatus under humid air and then in an homogenized soil and finally in field. The results evidenced that the screen printed film was able to give a response for a soil matric potential from about 570 kPa, that is to say well below the wilting point in the used soil.

Description: Since the mechanical properties of single cells together with the intercellular adhesive properties determine the macro-mechanical properties of plants, a method for evaluation of the cell elastic properties is needed to help explanation of the behavior of fruits and vegetables in handling and food processing. For this purpose, indentation of tomato mesocarp cells with an atomic force microscope was used. The Young’s modulus of a cell using the Hertz and Sneddon models, and stiffness were calculated from force-indentation curves. Use of two probes of distinct radius of curvature (20 nm and 10,000 nm) showed that the measured elastic properties were significantly affected by tip geometry. The Young’s modulus was about 100 kPa ± 35 kPa and 20 kPa ± 14 kPa for the sharper tip and a bead tip, respectively. Moreover, large variability regarding elastic properties (>100%) among cells sampled from the same region in the fruit was observed. We showed that AFM provides the possibility of combining nano-mechanical properties with topography imaging, which could be very useful for the study of structure-related properties of fruits and vegetables at the cellular and sub-cellular scale.

Description: Active magnetic bearings (AMBs) have become a key technology in various industrial applications. Self-sensing AMBs provide an integrated sensorless solution for position estimation, consolidating the sensing and actuating functions into a single electromagnetic transducer. The approach aims to reduce possible hardware failure points, production costs, and system complexity. Despite these advantages, self-sensing methods must address various technical challenges to maximize the performance thereof. This paper presents the direct current measurement (DCM) approach for self-sensing AMBs, denoting the direct measurement of the current ripple component. In AMB systems, switching power amplifiers (PAs) modulate the rotor position information onto the current waveform. Demodulation self-sensing techniques then use bandpass and lowpass filters to estimate the rotor position from the voltage and current signals. However, the additional phase-shift introduced by these filters results in lower stability margins. The DCM approach utilizes a novel PA switching method that directly measures the current ripple to obtain duty-cycle invariant position estimates. Demodulation filters are largely excluded to minimize additional phase-shift in the position estimates. Basic functionality and performance of the proposed self-sensing approach are demonstrated via a transient simulation model as well as a high current (10 A) experimental system. A digital implementation of amplitude modulation self-sensing serves as a comparative estimator.

Description: The stability of radiance measurements taken by the Sky Quality Meter (SQM)was tested under rapidly changing temperature conditions during exposure to a stable lightfield in the laboratory. The reported radiance was found to be negatively correlated withtemperature, but remained within 7% of the initial reported radiance over a temperaturerange of -15 °C to 35 °C, and during temperature changes of -33 °C/h and +70 °C/h.This is smaller than the manufacturer’s quoted unit-to-unit systematic uncertainty of 10%,indicating that the temperature compensation of the SQM is adequate under expected outdooroperating conditions.

Description: High-entropy (H-E) alloys, bulk metallic glasses (BMGs) and high-entropy BMGs (HE-BMGs) were statistically analyzed with the help of a database of ternary amorphous alloys. Thermodynamic quantities corresponding to heat of mixing and atomic size differences were calculated as a function of composition of the multicomponent alloys. Actual calculations were performed for configurational entropy (Sconfig.) in defining the H-E alloys and mismatch entropy (Ss) normalized with Boltzmann constant (kB), together with mixing enthalpy (DHmix) based on Miedema’s empirical model and Delta parameter (d) as a corresponding parameter to Ss/kB. The comparison between DHmix–d and DHmix–  diagrams for the ternary amorphous alloys revealed Ss/kB ~ (d /22)2. The zones S, S′ and B’s where H-E alloys with disordered solid solutions, ordered alloys and BMGs are plotted in the DHmix–d diagram are correlated with the areas in the DHmix – Ss /kB diagram. The results provide mutual understandings among H-E alloys, BMGs and HE-BMGs.

Description: This paper investigates the linear separation requirements for Angle-of-Arrival (AoA) and range sensors, in order to achieve the optimal performance in estimating the position of a target from multiple and typically noisy sensor measurements. We analyse the sensor-target geometry in terms of the Cramer–Rao inequality and the corresponding Fisher information matrix, in order to characterize localization performance with respect to the linear spatial distribution of sensors. Here in this paper, we consider both fixed and adjustable linear sensor arrays.

Description: The problem of drifting charge-induced currents is considered in order to predict the pulsed operational characteristics in photo-and particle-detectors with a junction controlled active area. The direct analysis of the field changes induced by drifting charge in the abrupt junction devices with a plane-parallel geometry of finite area electrodes is presented. The problem is solved using the one-dimensional approach. The models of the formation of the induced pulsed currents have been analyzed for the regimes of partial and full depletion. The obtained solutions for the current density contain expressions of a velocity field dependence on the applied voltage, location of the injected surface charge domain and carrier capture parameters. The drift component of this current coincides with Ramo’s expression. It has been illustrated, that the synchronous action of carrier drift, trapping, generation and diffusion can lead to a vast variety of possible current pulse waveforms. Experimental illustrations of the current pulse variations determined by either the rather small or large carrier density within the photo-injected charge domain are presented, based on a study of Si detectors.

Description: A visible light communication (VLC) system using an organic bulk heterojunction photodetector (OPD) is presented. The system has been successfully proven indoors with an audio signal. The emitter consists of three commercial high-power white LEDs connected in parallel. The receiver is based on an organic photodetector having as active layer a blend of poly(3-hexylthiophene) (P3HT) and phenyl C61-butyric acid methyl ester (PCBM). The OPD is opto-electrically characterized, showing a responsivity of 0.18 A/W and a modulation response of 790 kHz at −6 V.

Description: Applying the particle filter (PF) technique, this paper proposes a PF-based algorithm to blindly demodulate the chaotic direct sequence spread spectrum (CDS-SS) signals under the colored or non-Gaussian noises condition. To implement this algorithm, the PFs are modified by (i) the colored or non-Gaussian noises are formulated by autoregressive moving average (ARMA) models, and then the parameters that model the noises are included in the state vector; (ii) the range-differentiating factor is imported into the intruder’s chaotic system equation. Since the range-differentiating factor is able to make the inevitable chaos fitting error advantageous based on the chaos fitting method, thus the CDS-SS signals can be demodulated according to the range of the estimated message. Simulations show that the proposed PF-based algorithm can obtain a good bit-error rate performance when extracting the original binary message from the CDS-SS signals without any knowledge of the transmitter’s chaotic map, or initial value, even when colored or non-Gaussian noises exist.

Description: Model membrane approaches have attracted much attention in biomedical sciences to investigate and simulate biological processes. The application of model membrane systems for biosensor measurements is partly restricted by the fact that the integrity of membranes critically depends on the maintenance of an aqueous surrounding, while various biosensors require a preconditioning of dry sensors. This is for example true for the well-established surface acoustic wave (SAW) biosensor SAM®5 blue. Here, a simple drying procedure of sensor-supported model membranes is introduced using the protective disaccharide trehalose. Highly reproducible model membranes were prepared by the Langmuir-Blodgett technique, transferred to SAW sensors and supplemented with a trehalose solution. Membrane rehydration after dry incorporation into the SAW device becomes immediately evident by phase changes. Reconstituted model membranes maintain their full functionality, as indicated by biotin/avidin binding experiments. Atomic force microscopy confirmed the morphological invariability of dried and rehydrated membranes. Approximating to more physiological recognition phenomena, the site-directed immobilization of the integrin VLA-4 into the reconstituted model membrane and subsequent VCAM-1 ligand binding with nanomolar affinity were illustrated. This simple drying procedure is a novel way to combine the model membrane generation by Langmuir-Blodgett technique with SAW biosensor measurements, which extends the applicability of SAM®5 blue in biomedical sciences.

Description: Hull cleaning before repainting is a key operation in the maintenance of ships. For years, a method to improve such operation has been sought by means of the robotization of techniques such as grit blasting and ultra high pressure water jetting. Despite this, it continues to be standard practice in shipyards that this process is carried out manually because the developed robotized systems are too expensive to be widely accepted by shipyards. We have chosen to apply a more conservative and realistic approach to this problem, which has resulted in the development of several solutions that have been designed with different automation and operation range degrees. These solutions are fitted with most of the elements already available in many shipyards, so the installation of additional machinery in the workplace would not be necessary. This paper describes the evolutionary development of sensor systems for the automation of the preparation process of ship hull surfaces before the painting process is performed. Such evolution has given rise to the development of new technologies for coating removal.

Description: Stress corrosion cracks (SCC) in low-pressure steam turbine discs are serious hidden dangers to production safety in the power plants, and knowing the orientation and depth of the initial cracks is essential for the evaluation of the crack growth rate, propagation direction and working life of the turbine disc. In this paper, a method based on phased array ultrasonic transducer and artificial neural network (ANN), is proposed to estimate both the depth and orientation of initial cracks in the turbine discs. Echo signals from cracks with different depths and orientations were collected by a phased array ultrasonic transducer, and the feature vectors were extracted by wavelet packet, fractal technology and peak amplitude methods. The radial basis function (RBF) neural network was investigated and used in this application. The final results demonstrated that the method presented was efficient in crack estimation tasks.

Description: Recently, the duality between values (words) and orderings (permutations) has been proposed by the authors as a basis to discuss the relationship between information theoretic measures for finite-alphabet stationary stochastic processes and their permutatio nanalogues. It has been used to give a simple proof of the equality between the entropy rate and the permutation entropy rate for any finite-alphabet stationary stochastic process and to show some results on the excess entropy and the transfer entropy for finite-alphabet stationary ergodic Markov processes. In this paper, we extend our previous results to hidden Markov models and show the equalities between various information theoretic complexity and coupling measures and their permutation analogues. In particular, we show the following two results within the realm of hidden Markov models with ergodic internal processes: the two permutation analogues of the transfer entropy, the symbolic transfer entropy and the transfer entropy on rank vectors, are both equivalent to the transfer entropy if they are considered as the rates, and the directed information theory can be captured by the permutation entropy approach.

Description: The sustainability of agricultural production in the twenty-first century, both in industrialized and developing countries, benefits from the integration of farm management with information technology such that individual plants, rows, or subfields may be endowed with a singular “identity.” This approach approximates the nature of agricultural processes to the engineering of industrial processes. In order to cope with the vast variability of nature and the uncertainties of agricultural production, the concept of crop biometrics is defined as the scientific analysis of agricultural observations confined to spaces of reduced dimensions and known position with the purpose of building prediction models. This article develops the idea of crop biometrics by setting its principles, discussing the selection and quantization of biometric traits, and analyzing the mathematical relationships among measured and predicted traits. Crop biometric maps were applied to the case of a wine-production vineyard, in which vegetation amount, relative altitude in the field, soil compaction, berry size, grape yield, juice pH, and grape sugar content were selected as biometric traits. The enological potential of grapes was assessed with a quality-index map defined as a combination of titratable acidity, sugar content, and must pH. Prediction models for yield and quality were developed for high and low resolution maps, showing the great potential of crop biometric maps as a strategic tool for vineyard growers as well as for crop managers in general, due to the wide versatility of the methodology proposed.

Description: The paper discusses methods of evaluating thermodynamic properties of landscape cover based on multi-spectral measurements by the Landsat satellites. Authors demonstrate how these methods could be used for studying functionality of landscapes and for spatial interpolation of Flux NET system measurements.

Description: Proteobacteria produce N-acylhomoserine lactones as signaling molecules, which will bind to their cognate receptor and activate quorum sensing-mediated phenotypes in a population-dependent manner. Although quorum sensing signaling molecules can be degraded by bacteria or fungi, there is no reported work on the degradation of such molecules by basidiomycetous yeast. By using a minimal growth medium containing N-3-oxohexanoylhomoserine lactone as the sole source of carbon, a wetland water sample from Malaysia was enriched for microbial strains that can degrade N-acylhomoserine lactones, and consequently, a basidiomycetous yeast strain WW1C was isolated. Morphological phenotype and molecular analyses confirmed that WW1C was a strain of Trichosporon loubieri. We showed that WW1C degraded AHLs with N-acyl side chains ranging from 4 to 10 carbons in length, with or without oxo group substitutions at the C3 position. Re-lactonisation bioassays revealed that WW1C degraded AHLs via a lactonase activity. To the best of our knowledge, this is the first report of degradation of N-acyl-homoserine lactones and utilization of N-3-oxohexanoylhomoserine as carbon and nitrogen source for growth by basidiomycetous yeast from tropical wetland water; and the degradation of bacterial quorum sensing molecules by an eukaryotic yeast.

Description: This paper presents a bio-inspired networking strategy to support the cooperation between static sensors on the ground and mobile sensors in the air to perform surveillance missions in large areas. The goal of the proposal is to provide low overhead in the communication among sensor nodes, while allocating the mobile sensors to perform sensing activities requested by the static ones. Simulations have shown that the strategy is efficient in maintaining low overhead and achieving the desired coordination.

Description: In the face recognition field, principal component analysis is essential to the reduction of the image dimension. In spite of frequent use of this analysis, it is commonly believed that the basis faces with large eigenvalues are chosen as the best subset in the nearest neighbor classifiers. We propose an alternative that can predict the classification error during the training steps and find the useful basis faces for the similarity metrics of the classical pattern algorithms. In addition, we also show the need for the eye-aligned dataset to have the pure face. The experiments using face images verify that our method reduces the negative effect on the misaligned face images and decreases the weights of the useful basis faces in order to improve the classification accuracy.

Description: Automatic detection of pig wasting diseases is an important issue in the management of group-housed pigs. Further, respiratory diseases are one of the main causes of mortality among pigs and loss of productivity in intensive pig farming. In this study, we propose an efficient data mining solution for the detection and recognition of pig wasting diseases using sound data in audio surveillance systems. In this method, we extract the Mel Frequency Cepstrum Coefficients (MFCC) from sound data with an automatic pig sound acquisition process, and use a hierarchical two-level structure: the Support Vector Data Description (SVDD) and the Sparse Representation Classifier (SRC) as an early anomaly detector and a respiratory disease classifier, respectively. Our experimental results show that this new method can be used to detect pig wasting diseases both economically (even a cheap microphone can be used) and accurately (94% detection and 91% classification accuracy), either as a standalone solution or to complement known methods to obtain a more accurate solution.

Description: Automated methods of real-time, unobtrusive, human ambulation, activity, and wellness monitoring and data analysis using various algorithmic techniques have been subjects of intense research. The general aim is to devise effective means of addressing the demands of assisted living, rehabilitation, and clinical observation and assessment through sensor-based monitoring. The research studies have resulted in a large amount of literature. This paper presents a holistic articulation of the research studies and offers comprehensive insights along four main axes: distribution of existing studies; monitoring device framework and sensor types; data collection, processing and analysis; and applications, limitations and challenges. The aim is to present a systematic and most complete study of literature in the area in order to identify research gaps and prioritize future research directions.

Description: In this work, we introduce a generalization of the differential polynomial neural network utilizing fractional calculus. Fractional calculus is taken in the sense of the Caputo differential operator. It approximates a multi-parametric function with particular polynomials characterizing its functional output as a generalization of input patterns. This method can be employed on data to describe modelling of complex systems. Furthermore, the total information is calculated by using the fractional Poisson process.

Description: The corrosion of reinforcements induced by chloride has resulted to be one of the most frequent causes of their premature damage. Most corrosion sensors were designed to monitor corrosion state in concrete, such as Anode-Ladder-System and Corrowatch System, which are widely used to monitor chloride ingress in marine concrete. However, the monitoring principle of these corrosion sensors is based on the macro-cell test method, so erroneous information may be obtained, especially from concrete under drying or saturated conditions due to concrete resistance taking control in macro-cell corrosion. In this paper, a fast weak polarization method to test corrosion state of reinforcements based on electrochemical polarization dynamics was proposed. Furthermore, a new corrosion sensor for monitoring the corrosion state of concrete cover was developed based on the proposed test method. The sensor was tested in cement mortar, with dry-wet cycle tests to accelerate the chloride ingress rate. The results show that the corrosion sensor can effectively monitor chloride penetration into concrete with little influence of the relative humidity in the concrete. With a reasonable corrosion sensor electrode arrangement, it seems the Ohm-drop effect measured by EIS can be ignored, which makes the tested electrochemical parameters more accurate.

Description: This study describes a wireless laser displacement sensor node that measures displacement as a representative damage index for structural health monitoring (SHM). The proposed measurement system consists of a laser displacement sensor (LDS) and a customized wireless sensor node. Wireless communication is enabled by a sensor node that consists of a sensor module, a code division multiple access (CDMA) communication module, a processor, and a power module. An LDS with a long measurement distance is chosen to increase field applicability. For a wireless sensor node driven by a battery, we use a power control module with a low-power processor, which facilitates switching between the sleep and active modes, thus maximizing the power consumption efficiency during non-measurement and non-transfer periods. The CDMA mode is also used to overcome the limitation of communication distance, which is a challenge for wireless sensor networks and wireless communication. To evaluate the reliability and field applicability of the proposed wireless displacement measurement system, the system is tested onsite to obtain the required vertical displacement measurements during the construction of mega-trusses and an edge truss, which are the primary structural members in a large-scale irregular building currently under construction. The measurement values confirm the validity of the proposed wireless displacement measurement system and its potential for use in safety evaluations of structural elements.

Description: Bacterial cell-to-cell communication (quorum sensing) refers to the regulation of bacterial gene expression in response to changes in microbial population density. Quorum sensing bacteria produce, release and respond to chemical signal molecules called autoinducers. Bacteria use two types of autoinducers, namely autoinducer-1 (AI-1) and autoinducer-2 (AI-2) where the former are N-acylhomoserine lactones and the latter is a product of the luxS gene. Most of the reported literatures show that the majority of oral bacteria use AI-2 for quorum sensing but rarely the AI-1 system. Here we report the isolation of Pseudomonas putida strain T2-2 from the oral cavity. Using high resolution mass spectrometry, it is shown that this isolate produced N-octanoylhomoserine lactone (C8-HSL) and N-dodecanoylhomoserine lactone (C12-HSL) molecules. This is the first report of the finding of quorum sensing of P. putida strain T2-2 isolated from the human tongue surface and their quorum sensing molecules were identified.

Description: Presented here is a slotted-quad-beam structure sensor for the measurement of friction in micro bearings. Stress concentration slots are incorporated into a conventional quad-beam structure to improve the sensitivity of force measurements. The performance comparison between the quad-beam structure sensor and the slotted-quad-beam structure sensor are performed by theoretical modeling and finite element (FE) analysis. A hollow stainless steel probe is attached to the mesa of the sensor chip by a tailor-made organic glass fixture. Concerning the overload protection of the fragile beams, a glass wafer is bonded onto the bottom of sensor chip to limit the displacement of the mesa. The calibration of the packaged device is experimentally performed by a tri-dimensional positioning stage, a precision piezoelectric ceramic and an electronic analytical balance, which indicates its favorable sensitivity and overload protection. To verify the potential of the proposed sensor being applied in micro friction measurement, a measurement platform is established. The output of the sensor reflects the friction of bearing resulting from dry friction and solid lubrication. The results accord with the theoretical modeling and demonstrate that the sensor has the potential application in measuring the micro friction force under stable stage in MEMS machines.

Description: A novel approach for identifying explosive species is reported, using Raman spectroscopy in suspended core optical fibers. Numerical simulations are presented that predict the strength of the observed signal as a function of fiber geometry, with the calculated trends verified experimentally and used to optimize the sensors. This technique is used to identify hydrogen peroxide in water solutions at volumes less than 60 nL and to quantify microgram amounts of material using the solvent’s Raman signature as an internal calibration standard. The same system, without further modifications, is also used to detect 1,4-dinitrobenzene, a model molecule for nitrobenzene-based explosives such as 2,4,6-trinitrotoluene (TNT).

Description: In the bacteria kingdom, quorum sensing (QS) is a cell-to-cell communication that relies on the production of and response to specific signaling molecules. In proteobacteria, N-acylhomoserine lactones (AHLs) are the well-studied signaling molecules. The present study aimed to characterize the production of AHL of a bacterial strain A9 isolated from a Malaysian tropical soil. Strain A9 was identified as Burkholderia sp. using matrix-assisted laser desorption ionization-time-of-flight mass spectrometry and 16S rDNA nucleotide sequence analysis. AHL production by A9 was detected with two biosensors, namely Chromobacterium violaceum CV026 and Escherichia coli [pSB401]. Thin layer chromatography results showed N–hexanoylhomoserine lactone (C6-HSL) and N–octanoylhomoserine lactone (C8-HSL) production. Unequivocal identification of C6-HSL and C8-HSL was achieved by high resolution triple quadrupole liquid chromatography-mass spectrometry analysis. We have demonstrated that Burkholderia sp. strain A9 produces AHLs that are known to be produced by other Burkholderia spp. with CepI/CepR homologs.

Description: In this paper, we present an approach to sense human body capacitance and apply it to recognize lower limb locomotion modes. The proposed wearable sensing system includes sensing bands, a signal processing circuit and a gait event detection module. Experiments on long-term working stability, adaptability to disturbance and locomotion mode recognition are carried out to validate the effectiveness of the proposed approach. Twelve able-bodied subjects are recruited, and eleven normal gait modes are investigated. With an event-dependent linear discriminant analysis classifier and feature selection procedure, four time-domain features are used for pattern recognition and satisfactory recognition accuracies (97:3% ± 0:5%, 97:0% ± 0:4%, 95:6% ± 0:9% and 97:0% ± 0:4% for four phases of one gait cycle respectively) are obtained. The accuracies are comparable with that from electromyography-based systems and inertial-based systems. The results validate the effectiveness of the proposed lower limb capacitive sensing approach in recognizing human normal gaits.

Description: Projector-camera systems are currently used in a wide field of applications, such as 3D reconstruction and augmented reality, and can provide accurate measurements, depending on the configuration and calibration. Frequently, the calibration task is divided into two steps: camera calibration followed by projector calibration. The latter still poses certain problems that are not easy to solve, such as the difficulty in obtaining a set of 2D–3D points to compute the projection matrix between the projector and the world. Existing methods are either not sufficiently accurate or not flexible. We propose an easy and automatic method to calibrate such systems that consists in projecting a calibration pattern and superimposing it automatically on a known printed pattern. The projected pattern is provided by a virtual camera observing a virtual pattern in an OpenGL model. The projector displays what the virtual camera visualizes. Thus, the projected pattern can be controlled and superimposed on the printed one with the aid of visual servoing. Our experimental results compare favorably with those of other methods considering both usability and accuracy.

Description: The world-wide sensor web has become a very useful technique for monitoring the physical world at spatial and temporal scales that were previously impossible. Yet we believe that the full potential of sensor web has thus far not been revealed. In order to harvest the world-wide sensor web’s full potential, a geospatial cyberinfrastructure is needed to store, process, and deliver large amount of sensor data collected worldwide. In this paper, we first define the issue of the sensor web long tail followed by our view of the world-wide sensor web architecture. Then, we introduce the Geospatial Cyberinfrastructure for Environmental Sensing (GeoCENS) architecture and explain each of its components. Finally, with demonstration of three real-world powered-by-GeoCENS sensor web applications, we believe that the GeoCENS architecture can successfully address the sensor web long tail issue and consequently realize the world-wide sensor web vision.

Description: Impact detection in aeronautical structures allows predicting their future reliability and performance. An impact can produce microscopic fissures that could evolve into fractures or even the total collapse of the structure, so it is important to know the location and severity of each impact. For this purpose, optical fibers with Bragg gratings are used to analyze each impact and the vibrations generated by them. In this paper it is proven that optical fibers with Bragg gratings can be used to detect impacts, and also that a high-frequency interrogator is necessary to collect valuable information about the impacts. The use of two interrogators constitutes the main novelty of this paper.

Description: The Rational Function Model (RFM) has been widely used as an alternative to rigorous sensor models of high-resolution optical imagery in photogrammetry and remote sensing geometric processing. However, not much work has been done to evaluate the applicability of the RF model for Synthetic Aperture Radar (SAR) image processing. This paper investigates how to generate a Rational Polynomial Coefficient (RPC) for high-resolution TerraSAR-X imagery using an independent approach. The experimental results demonstrate that the RFM obtained using the independent approach fits the Range-Doppler physical sensor model with an accuracy of greater than 10−3 pixel. Because independent RPCs indicate absolute errors in geolocation, two methods can be used to improve the geometric accuracy of the RFM. In the first method, Ground Control Points (GCPs) are used to update SAR sensor orientation parameters, and the RPCs are calculated using the updated parameters. Our experiment demonstrates that by using three control points in the corners of the image, an accuracy of 0.69 pixels in range and 0.88 pixels in the azimuth direction is achieved. For the second method, we tested the use of an affine model for refining RPCs. In this case, by applying four GCPs in the corners of the image, the accuracy reached 0.75 pixels in range and 0.82 pixels in the azimuth direction.

Description: Currently there are a few fields of application using quartz crystal microbalances (QCM). Because of environmental conditions and insufficient resolution of the microbalance, chemical sensing of volatile organic compounds in an open system was as yet not possible. In this study we present strategies on how to use 195 MHz fundamental quartz resonators for a mobile sensor platform to detect airborne analytes. Commonly the use of devices with a resonant frequency of about 10 MHz is standard. By increasing the frequency to 195 MHz the frequency shift increases by a factor of almost 400. Unfortunately, such kinds of quartz crystals tend to exhibit some challenges to obtain a reasonable signal-to-noise ratio. It was possible to reduce the noise in frequency in a continuous air flow of 7.5 m/s to 0.4 Hz [i.e., σ(τ) = 2 × 10−9] by elucidating the major source of noise. The air flow in the vicinity of the quartz was analyzed to reduce turbulences. Furthermore, we found a dependency between the acceleration sensitivity and mechanical stress induced by an internal thermal gradient. By reducing this gradient, we achieved reduction of the sensitivity to acceleration by more than one decade. Hence, the resulting sensor is more robust to environmental conditions such as temperature, acceleration and air flow.

Description: In this study, readily available antibodies that are used in standard agglutination tests were evaluated for their use in ABO blood typing by a surface plasmon resonance imaging (SPR imaging) technique. Five groups of antibodies, including mixed clones of anti-A, anti-B, and anti-AB, and single clones of anti-A and anti-B, were used to construct the five-line detection arrays using a multichannel flow cell in the SPR imager. The red blood cell (RBC) samples were applied to a multichannel flow cell that was orthogonal to the detection line arrays for blood group typing. We found that the blood samples were correctly grouped in less than 12 min by the SPR imaging technique, and the results were consistent with those of the standard agglutination technique for all 60 samples. We found that mixed clones of antibodies provided 33%–68% greater change in the SPR signal than the single-clone antibodies. Applying the SPR imaging technique using readily available antibodies may reduce the costs of the antibodies, shorten the measurement time, and increase the throughput.

Description: In the case of through-the-wall localization of moving targets by ultra wideband (UWB) radars, there are applications in which handheld sensors equipped only with one transmitting and two receiving antennas are applied. Sometimes, the radar using such a small antenna array is not able to localize the target with the required accuracy. With a view to improve through-the-wall target localization, cooperative positioning based on a fusion of data retrieved from two independent radar systems can be used. In this paper, the novel method of the cooperative localization referred to as joining intersections of the ellipses is introduced. This method is based on a geometrical interpretation of target localization where the target position is estimated using a properly created cluster of the ellipse intersections representing potential positions of the target. The performance of the proposed method is compared with the direct calculation method and two alternative methods of cooperative localization using data obtained by measurements with the M-sequence UWB radars. The direct calculation method is applied for the target localization by particular radar systems. As alternative methods of cooperative localization, the arithmetic average of the target coordinates estimated by two single independent UWB radars and the Taylor series method is considered.

Description: In this paper, different polymer optical fibres for applications in force sensing systems in textile fabrics are reported. The proposed method is based on the deflection of the light in fibre waveguides. Applying a force on the fibre changes the geometry and affects the wave guiding properties and hence induces light loss in the optical fibre. Fibres out of three different elastic and transparent copolymer materials were successfully produced and tested. Moreover, the influence of the diameter on the sensing properties was studied. The detectable force ranges from 0.05 N to 40 N (applied on 3 cm of fibre length), which can be regulated with the material and the diameter of the fibre. The detected signal loss varied from 0.6% to 78.3%. The fibres have attenuation parameters between 0.16–0.25 dB/cm at 652 nm. We show that the cross-sensitivies to temperature, strain and bends are low. Moreover, the high yield strength (0.0039–0.0054 GPa) and flexibility make these fibres very attractive candidates for integration into textiles to form wearable sensors, medical textiles or even computing systems.

Description: Proton Transfer Reaction Mass Spectrometry (PTR-MS) has evolved in the last decade as a fast and high sensitivity sensor for the real-time monitoring of volatile compounds. Its applications range from environmental sciences to medical sciences, from food technology to bioprocess monitoring. Italian scientists and institutions participated from the very beginning in fundamental and applied research aiming at exploiting the potentialities of this technique and providing relevant methodological advances and new fundamental indications. In this review we describe this activity on the basis of the available literature. The Italian scientific community has been active mostly in food science and technology, plant physiology and environmental studies and also pioneered the applications of the recently released PTR-ToF-MS (Proton Transfer Reaction—Time of Flight—Mass Spectrometry) in food science and in plant physiology. In the very last years new results related to bioprocess monitoring and health science have been published as well. PTR-MS data analysis, particularly in the case of the ToF based version, and the application of advanced chemometrics and data mining are also aspects characterising the activity of the Italian community.

Description: Agriculture and Forestry are two broad and promising areas demanding technological solutions with the aim of increasing production or accurate inventories for sustainability while the environmental impact is minimized by reducing the application of agro-chemicals and increasing the use of environmental friendly agronomical practices. In addition, the immediate consequence of this “trend” is the reduction of production costs.

Description: Large amounts of low-grade heat are emitted by various industries and exhausted into the environment. This heat energy can be used as a free source for pyroelectric power generation. A three-dimensional pattern helps to improve the temperature variation rates in pyroelectric elements by means of lateral temperature gradients induced on the sidewalls of the responsive elements. A novel method using sandblast etching is successfully applied in fabricating the complex pattern of a vortex-like electrode. Both experiment and simulation show that the proposed design of the vortex-like electrode improved the electrical output of the pyroelectric cells and enhanced the efficiency of pyroelectric harvesting converters. A three-dimensional finite element model is generated by commercial software for solving the transient temperature fields and exploring the temperature variation rate in the PZT pyroelectric cells with various designs. The vortex-like type has a larger temperature variation rate than the fully covered type, by about 53.9%.The measured electrical output of the vortex-like electrode exhibits an obvious increase in the generated charge and the measured current, as compared to the fully covered electrode, by of about 47.1% and 53.1%, respectively.

Description: An analytic method for predicting the performance of track-to-track association (TTTA) with biased data in multi-sensor multi-target tracking scenarios is proposed in this paper. The proposed method extends the existing results of the bias-free situation by accounting for the impact of sensor biases. Since little insight of the intrinsic relationship between scenario parameters and the performance of TTTA can be obtained by numerical simulations, the proposed analytic approach is a potential substitute for the costly Monte Carlo simulation method. Analytic expressions are developed for the global nearest neighbor (GNN) association algorithm in terms of correct association probability. The translational biases of sensors are incorporated in the expressions, which provide good insight into how the TTTA performance is affected by sensor biases, as well as other scenario parameters, including the target spatial density, the extraneous track density and the average association uncertainty error. To show the validity of the analytic predictions, we compare them with the simulation results, and the analytic predictions agree reasonably well with the simulations in a large range of normally anticipated scenario parameters.

Description: A crucial aspect in rowing is having a synchronized, highly-efficient stroke. This is very difficult to obtain, due to the many interacting factors that each rower of the crew must perceive. Having a system that monitors and represents the crew coordination would be of great help to the coach during training sessions. In the literature, some methods already employ wireless sensors for capturing motion patterns that affect rowing performance. A challenging problem is to support the coach’s decisions at his same level of knowledge, using a limited number of sensors and avoiding the complexity of the biomechanical analysis of human movements. In this paper, we present a multi-agent information-processing system for on-water measuring of both the overall crew asynchrony and the individual rower asynchrony towards the crew. More specifically, in the system, the first level of processing is managed by marking agents, which release marks in a sensing space, according to the rowers’ motion. The accumulation of marks enables a stigmergic cooperation mechanism, generating collective marks, i.e., short-term memory structures in the sensing space. At the second level of processing, information provided by marks is observed by similarity agents, which associate a similarity degree with respect to optimal marks. Finally, the third level is managed by granulation agents, which extract asynchrony indicators for different purposes. The effectiveness of the system has been experimented on real-world scenarios. The study includes the problem statement and its characterization in the literature, as well as the proposed solving approach and initial experimental setting.

Description: Considering the characteristics of wind tunnel tests, a position measurement system that can minimize the effects on the flow of simulated wind must be established. In this study, a motion-capture camera was used to measure the displacement responses of structures in a wind tunnel test, and the applicability of the system was tested. A motion-capture system (MCS) could output 3D coordinates using two-dimensional image coordinates obtained from the camera. Furthermore, this remote sensing system had some flexibility regarding lab installation because of its ability to measure at relatively long distances from the target structures. In this study, we performed wind tunnel tests on a pylon specimen and compared the measured responses of the MCS with the displacements measured with a laser displacement sensor (LDS). The results of the comparison revealed that the time-history displacement measurements from the MCS slightly exceeded those of the LDS. In addition, we confirmed the measuring reliability of the MCS by identifying the dynamic properties (natural frequency, damping ratio, and mode shape) of the test specimen using system identification methods (frequency domain decomposition, FDD). By comparing the mode shape obtained using the aforementioned methods with that obtained using the LDS, we also confirmed that the MCS could construct a more accurate mode shape (bending-deflection mode shape) with the 3D measurements.

Description: Seismic data is difficult to analyze and classical mathematical tools reveal strong limitations in exposing hidden relationships between earthquakes. In this paper, we study earthquake phenomena in the perspective of complex systems. Global seismic data, covering the period from 1962 up to 2011 is analyzed. The events, characterized by their magnitude, geographic location and time of occurrence, are divided into groups, either according to the Flinn-Engdahl (F-E) seismic regions of Earth or using a rectangular grid based in latitude and longitude coordinates. Two methods of analysis are considered and compared in this study. In a first method, the distributions of magnitudes are approximated by Gutenberg-Richter (G-R) distributions and the parameters used to reveal the relationships among regions. In the second method, the mutual information is calculated and adopted as a measure of similarity between regions. In both cases, using clustering analysis, visualization maps are generated, providing an intuitive and useful representation of the complex relationships that are present among seismic data. Such relationships might not be perceived on classical geographic maps. Therefore, the generated charts are a valid alternative to other visualization tools, for understanding the global behavior of earthquakes.

Description: We investigate solutions of a generalized diffusion equation that contains nonlinear terms in the presence of external forces and reaction terms. The solutions found here can have a compact or long tail behavior and can be expressed in terms of the q-exponential functions present in the Tsallis framework. In the case of the long-tailed behavior, in the asymptotic limit, these solutions can also be connected with the L´evy distributions. In addition, from the results presented here, a rich class of diffusive processes, including normal and anomalous ones, can be obtained.

Description: Oil sand pumps are widely used in the mining industry for the delivery of mixtures of abrasive solids and liquids. Because they operate under highly adverse conditions, these pumps usually experience significant wear. Consequently, equipment owners are quite often forced to invest substantially in system maintenance to avoid unscheduled downtime. In this study, an approach combining relevance vector machines (RVMs) with a sum of two exponential functions was developed to predict the remaining useful life (RUL) of field pump impellers. To handle field vibration data, a novel feature extracting process was proposed to arrive at a feature varying with the development of damage in the pump impellers. A case study involving two field datasets demonstrated the effectiveness of the developed method. Compared with standalone exponential fitting, the proposed RVM-based model was much better able to predict the remaining useful life of pump impellers.

Description: The time-average method currently available is limited to analyzing the specific performance of the automatic gain control-proportional and integral (AGC-PI) based velocity-controlled closed-loop in a micro-electro-mechanical systems (MEMS) vibratory gyroscope, since it is hard to solve nonlinear functions in the time domain when the control loop reaches to 3rd order. In this paper, we propose a linearization design approach to overcome this limitation by establishing a 3rd order linear model of the control loop and transferring the analysis to the frequency domain. Order reduction is applied on the built linear model’s transfer function by constructing a zero-pole doublet, and therefore mathematical expression of each control loop’s performance specification is obtained. Then an optimization methodology is summarized, which reveals that a robust, stable and swift control loop can be achieved by carefully selecting the system parameters following a priority order. Closed-loop drive circuits are designed and implemented using 0.35 μm complementary metal oxide semiconductor (CMOS) process, and experiments carried out on a gyroscope prototype verify the optimization methodology that an optimized stability of the control loop can be achieved by constructing the zero-pole doublet, and disturbance rejection capability (D.R.C) of the control loop can be improved by increasing the integral term.

Description: Centrifugal compressors are a key piece of equipment for modern production. Among the components of the centrifugal compressor, the impeller is a pivotal part as it is used to transform kinetic energy into pressure energy. Blade crack condition monitoring and classification has been broadly investigated in the industrial and academic area. In this research, a pressure pulsation (PP) sensor arranged in close vicinity to the crack area and the corresponding casing vibration signals are used to monitor blade crack information. As these signals cannot directly demonstrate the blade crack, the method employed in this research is based on the extraction of weak signal characteristics that are induced by blade cracking. A method for blade crack classification based on the signals monitored by using a squared envelope spectrum (SES) is presented. Experimental investigations on blade crack classification are carried out to verify the effectiveness of this method. The results show that it is an effective tool for blade crack classification in centrifugal compressors.

Description: This paper presents a CMOS temperature sensor based on the thermal dependencies of the leakage currents targeting the 65 nm node. To compensate for the effect of process fluctuations, the proposed sensor realizes the ratio of two measures of the time it takes a capacitor to discharge through a transistor in the subthreshold regime. Furthermore, a novel charging mechanism for the capacitor is proposed to further increase the robustness against fabrication variability. The sensor, including digitization and interfacing, occupies 0.0016 mm2 and has an energy consumption of 47.7–633 pJ per sample. The resolution of the sensor is 0.28 °C, and the 3σ inaccuracy over the range 40–110 °C is 1.17 °C.

Description: This paper presents a low-cost hyperspectral measurement setup in a new application based on fluorescence detection in the visible (Vis) wavelength range. The aim of the setup is to take hyperspectral fluorescence images of viscous materials. Based on these images, fluorescent and non-fluorescent impurities in the viscous materials can be detected. For the illumination of the measurement object, a narrow-band high-power light-emitting diode (LED) with a center wavelength of 370 nm was used. The low-cost acquisition unit for the imaging consists of a linear variable filter (LVF) and a complementary metal oxide semiconductor (CMOS) 2D sensor array. The translucent wavelength range of the LVF is from 400 nm to 700 nm. For the confirmation of the concept, static measurements of fluorescent viscous materials with a non-fluorescent impurity have been performed and analyzed. With the presented setup, measurement surfaces in the micrometer range can be provided. The measureable minimum particle size of the impurities is in the nanometer range. The recording rate for the measurements depends on the exposure time of the used CMOS 2D sensor array and has been found to be in the microsecond range.

Description: Since most experimental observations are performed at constant temperature and pressure, the isothermal-isobaric (NPT) ensemble has been widely used in molecular simulations. Nevertheless, the NPT ensemble has only recently been placed on a rigorous foundation. The proper formulation of the NPT ensemble requires a “shell” particle to uniquely identify the volume of the system, thereby avoiding the redundant counting of configurations. Here, we review our recent work in incorporating a shell particle into molecular dynamics simulation algorithms to generate the correct NPT ensemble averages. Unlike previous methods, a piston of unknown mass is no longer needed to control the response time of the volume fluctuations. As the volume of the system is attached to the shell particle, the system itself now sets the time scales for volume and pressure fluctuations. Finally, we discuss a number of tests that ensure the equations of motion sample phase space correctly and consider the response time of the system to pressure changes with and without the shell particle. Overall, the shell particle algorithm is an effective simulation method for studying systems exposed to a constant external pressure and may provide an advantage over other existing constant pressure approaches when developing nonequilibrium molecular dynamics methods.

Description: We review a nonparametric version of Amari’s information geometry in which the set of positive probability densities on a given sample space is endowed with an atlas of charts to form a differentiable manifold modeled on Orlicz Banach spaces. This nonparametric setting is used to discuss the setting of typical problems in machine learning and statistical physics, such as black-box optimization, Kullback-Leibler divergence, Boltzmann-Gibbs entropy and the Boltzmann equation.

Description: Polymers of hydrogen cyanide and their hydrolysis products constitute a plausible, but still poorly understood proposal for early prebiotic chemistry on Earth. HCN polymers are generated by the interplay of more than a dozen distinctive reaction mechanisms and form a highly complex mixture. Here we use a computational model based on graph grammars as a means of exploring the chemical spaces of HCN polymerization and hydrolysis. A fundamental issue is to understand the combinatorial explosion inherent in large, complex chemical systems. We demonstrate that experimental data, here obtained by mass spectrometry, and computationally predicted free energies together can be used to guide the exploration of the chemical space and makes it feasible to investigate likely pathways and chemical motifs even in potentially open-ended chemical systems.

Description: We study the phenomenon of periodic pulling which occurs in certain integrated microcircuits of relevant interest in applications, namely the injection-locked frequency dividers (ILFDs). They are modelled as second-order driven oscillators working in the subharmonic (secondary) resonance regime, i.e., when the self-oscillating frequency is close (resonant) to an integer submultiple n of the driving frequency. Under the assumption of weak injection, we find the spectrum of the system’s oscillatory response in the unlocked mode through closed-form expressions, showing that such spectrum is double-sided and asymmetric, unlike the single-sided spectrum of systems with primary resonance (n=1). An analytical expression for the amplitude modulation of the oscillatory response is also presented. Numerical results are presented to support theoretical relations derived.

Description: An entropy for the scalar variable case, parallel to Havrda-Charvat entropy, was introduced by the first author, and the properties and its connection to Tsallis non-extensive statistical mechanics and the Mathai pathway model were examined by the authors in previous papers. In the current paper, we extend the entropy to cover the scalar case, multivariable case, and matrix variate case. Then, this measure is optimized under different types of restrictions, and a number of models in the multivariable case and matrix variable case are obtained. Connections of these models to problems in statistical and physical sciences are pointed out. An application of the simplest case of the pathway model to the interpretation of solar neutrino data by applying standard deviation analysis and diffusion entropy analysis is provided.

Description: First, this paper recalls a recently introduced method of adaptive monitoring of dynamical systems and presents the most recent extension with a multiscale-enhanced approach. Then, it is shown that this concept of real-time data monitoring establishes a novel non-Shannon and non-probabilistic concept of novelty quantification, i.e., Entropy of Learning, or in short the Learning Entropy. This novel cognitive measure can be used for evaluation of each newly measured sample of data, or even of whole intervals. The Learning Entropy is quantified in respect to the inconsistency of data to the temporary governing law of system behavior that is incrementally learned by adaptive models such as linear or polynomial adaptive filters or neural networks. The paper presents this novel concept on the example of gradient descent learning technique with normalized learning rate.

Description: This article deals with the application of the principles of SCD (Selective Change Driven) vision to 3D laser scanning. Two experimental sets have been implemented: one with a classical CMOS (Complementary Metal-Oxide Semiconductor) sensor, and the other one with a recently developed CMOS SCD sensor for comparative purposes, both using the technique known as Active Triangulation. An SCD sensor only delivers the pixels that have changed most, ordered by the magnitude of their change since their last readout. The 3D scanning method is based on the systematic search through the entire image to detect pixels that exceed a certain threshold, showing the SCD approach to be ideal for this application. Several experiments for both capturing strategies have been performed to try to find the limitations in high speed acquisition/processing. The classical approach is limited by the sequential array acquisition, as predicted by the Nyquist

Description: DC-offset and DC-suppression are key parameters in bioelectric amplifiers. However, specific DC analyses are not often explained. Several factors influence the DC-budget: the programmable gain, the programmable cut-off frequencies for high pass filtering and, the low cut-off values and the capacitor blocking issues involved. A new intermediate stage is proposed to address the DC problem entirely. Two implementations were tested. The stage is composed of a programmable gain amplifier (PGA) with DC-rejection and low output offset. Cut-off frequencies are selectable and values from 0.016 to 31.83 Hz were tested, and the capacitor deblocking is embedded in the design. Hence, this PGA delivers most of the required gain with constant low output offset, notwithstanding the gain or cut-off frequency selected.

Description: This paper presents a method implemented in a system for automatic contactless calibration of gauge blocks designed at ISI ASCR. The system combines low-coherence interferometry and laser interferometry, where the first identifies the gauge block sides position and the second one measures the gauge block length itself. A crucial part of the system is the algorithm for gauge block alignment to the measuring beam which is able to compensate the gauge block lateral and longitudinal tilt up to 0.141 mrad. The algorithm is also important for the gauge block position monitoring during its length measurement.

Description: Smartphone-based activity recognition (SP-AR) recognizes users’ activities using the embedded accelerometer sensor. Only a small number of previous works can be classified as online systems, i.e., the whole process (pre-processing, feature extraction, and classification) is performed on the device. Most of these online systems use either a high sampling rate (SR) or long data-window (DW) to achieve high accuracy, resulting in short battery life or delayed system response, respectively. This paper introduces a real-time/online SP-AR system that solves this problem. Exploratory data analysis was performed on acceleration signals of 6 activities, collected from 30 subjects, to show that these signals are generated by an autoregressive (AR) process, and an accurate AR-model in this case can be built using a low SR (20 Hz) and a small DW (3 s). The high within class variance resulting from placing the phone at different positions was reduced using kernel discriminant analysis to achieve position-independent recognition. Neural networks were used as classifiers. Unlike previous works, true subject-independent evaluation was performed, where 10 new subjects evaluated the system at their homes for 1 week. The results show that our features outperformed three commonly used features by 40% in terms of accuracy for the given SR and DW.

Description: Spectroscopy has proven to be an efficient tool for measuring the properties of meat. In this article, hyperspectral imaging (HSI) techniques are used to determine the moisture content in cooked chicken breast over the VIS/NIR (400–1,000 nm) spectral range. Moisture measurements were performed using an oven drying method. A partial least squares regression (PLSR) model was developed to extract a relationship between the HSI spectra and the moisture content. In the full wavelength range, the PLSR model possessed a maximum  of 0.90 and an SEP of 0.74%. For the NIR range, the PLSR model yielded an  of 0.94 and an SEP of 0.71%. The majority of the absorption peaks occurred around 760 and 970 nm, representing the water content in the samples. Finally, PLSR images were constructed to visualize the dehydration and water distribution within different sample regions. The high correlation coefficient and low prediction error from the PLSR analysis validates that HSI is an effective tool for visualizing the chemical properties of meat.

Description: The paper presents a coaxial-like sensor operating in the 20 Hz–2 MHz frequency range used to determine the electrical properties of selected liquids of low electrical conductivity. Examined materials included low-concentrated aqueous solutions of potassium chloride, sodium chloride and trisodium citrate, which are common food additives. Impedance spectra of the measurement cell filled with particular liquids were obtained and analyzed using the electrical equivalent circuit approach. The values of physical quantities and parameters describing the equivalent circuit components, including a constant phase element, were calculated for each sample. The applied sensor was also calibrated for electrical conductivity measurements up to 8 mS/m. The constant phase element parameters differed among the studied solutions and concentrations. This may provide a basis for a detection method of small amounts of compounds, such as food additives in low-concentrated aqueous solutions. To demonstrate the potential of the presented method, samples of purchased mineral water and a flavored drink containing various additives were tested.

Description: An efficient and low cost optical method for directly measuring the concentration of homogenous biological solutes is proposed and demonstrated. The proposed system operates by Fresnel reflection, with a flat-cleaved single-mode fiber serving as the sensor probe. A laser provides a 12.9 dBm sensor signal at 1,550 nm, while a computer-controlled optical power meter measures the power of the signal returned by the probe. Three different mesenchymal stem cell (MSC) lines were obtained, sub-cultured and trypsinized daily over 9 days. Counts were measured using a haemocytometer and the conditioned media (CM) was collected daily and stored at −80 °C. MSCs release excretory biomolecules proportional to their growth rate into the CM, which changes the refractive index of the latter. The sensor is capable of detecting changes in the number of stem cells via correlation to the change in the refractive index of the CM, with the measured power loss decreasing approximately 0.4 dB in the CM sample per average 1,000 cells in the MSC subculture. The proposed system is highly cost-effective, simple to deploy, operate, and maintain, is non-destructive, and allows reliable real-time measurement of various stem cell proliferation parameters.

Description: This paper proposes and implements a new TDMA-based MAC protocol for providing timely and reliable delivery of data and command for monitoring and control networks. In this kind of network, sensor nodes are required to sense data from the monitoring environment periodically and then send the data to a sink. The sink determines whether the environment is safe or not by analyzing the acquired data. Sometimes, a command or control message is sent from the sink to a particular node or a group of nodes to execute the services or request further interested data. The proposed MAC protocol enables bidirectional communication, controls active and sleep modes of a sensor node to conserve energy, and addresses the problem of load unbalancing between the nodes near a sink and the other nodes. It can improve reliability of communication significantly while extending network lifetime. These claims are supported by the experimental results.

Description: To reduce time and cost of damage inspection, on-line impact monitoring of aircraft composite structures is needed. A digital monitor based on an array of piezoelectric transducers (PZTs) is developed to record the impact region of impacts on-line. It is small in size, lightweight and has low power consumption, but there are two problems with the impact alarm region localization method of the digital monitor at the current stage. The first one is that the accuracy rate of the impact alarm region localization is low, especially on complex composite structures. The second problem is that the area of impact alarm region is large when a large scale structure is monitored and the number of PZTs is limited which increases the time and cost of damage inspections. To solve the two problems, an impact alarm region imaging and localization method based on digital sequences and time reversal is proposed. In this method, the frequency band of impact response signals is estimated based on the digital sequences first. Then, characteristic signals of impact response signals are constructed by sinusoidal modulation signals. Finally, the phase synthesis time reversal impact imaging method is adopted to obtain the impact region image. Depending on the image, an error ellipse is generated to give out the final impact alarm region. A validation experiment is implemented on a complex composite wing box of a real aircraft. The validation results show that the accuracy rate of impact alarm region localization is approximately 100%. The area of impact alarm region can be reduced and the number of PZTs needed to cover the same impact monitoring region is reduced by more than a half.

Description: Mobile wireless multimedia sensor networks (WMSNs), which consist of mobile sink or sensor nodes and use rich sensing information, require much faster and more reliable wireless links than static wireless sensor networks (WSNs). This paper proposes an adaptive multi-node (MN) multiple input and multiple output (MIMO) transmission to improve the transmission reliability and capacity of mobile sink nodes when they experience spatial correlation. Unlike conventional single-node (SN) MIMO transmission, the proposed scheme considers the use of transmission antennas from more than two sensor nodes. To find an optimal antenna set and a MIMO transmission scheme, a MN MIMO channel model is introduced first, followed by derivation of closed-form ergodic capacity expressions with different MIMO transmission schemes, such as space-time transmit diversity coding and spatial multiplexing. The capacity varies according to the antenna correlation and the path gain from multiple sensor nodes. Based on these statistical results, we propose an adaptive MIMO mode and antenna set switching algorithm that maximizes the ergodic capacity of mobile sink nodes. The ergodic capacity of the proposed scheme is compared with conventional SN MIMO schemes, where the gain increases as the antenna correlation and path gain ratio increase.

Description: In this work we have developed a multiplex microarray system capable of detecting VEGF165 and thrombin. We recently described a Sandwich Aptamer Microarray (SAM) for thrombin detection feasible for use in multiplex microarrays; here we describe a new aptasensor for VEGF165 detection employing Vap7 and VEa5, two DNA aptamers recognizing different sites of the protein. The aptamers were modified to be adapted to the solid phase platform of SAM and their capability to simultaneously recognize VEGF165 by forming a ternary complex was analyzed in solution. Having so defined the best tandem arrangement of modified aptamers, we set up the aptasensor for VEGF165, and finally analyzed the multiplex system with the two aptasensors for the simultaneous detection of VEGF165 and thrombin. The results indicate that each sandwich is specific, even when the two proteins are mixed. The system performance is consistent with the behavior evidenced by the biochemical analysis, which proves to be valuable to drive the evaluation and refinement of aptamers prior to or along the development of a detection platform. Since thrombin upregulates VEGF expression, the simultaneous recognition of these two proteins could be useful in the analysis of biomarkers in pathologies characterized by neo-angiogenesis.

Description: Surface plasmon resonance (SPR) sensor is widely used for its high precision and real-time analysis. Fiber-optic SPR sensor is easy for miniaturization, so it is commonly used in the development of portable detection equipment. It can also be used for remote, real-time, and online detection. In this study, a wavelength modulation fiber-optic SPR sensor is designed, and theoretical analysis of optical propagation in the optical fiber is also done. Compared with existing methods, both the transmission of a skew ray and the influence of the chromatic dispersion are discussed. The resonance wavelength is calculated at two different cases, in which the chromatic dispersion in the fiber core is considered. According to the simulation results, a novel multi-channel fiber-optic SPR sensor is likewise designed to avoid defaults aroused by the complicated computation of the skew ray as well as the chromatic dispersion. Avoiding the impact of skew ray can do much to improve the precision of this kind of sensor.

Description: A simple two-step method was employed for preparing nano-sized gold nanoparticles-graphene composite to construct a GNPs-GR-SDS modified electrode. Hemoglobin (Hb) was successfully immobilized on the surface of a basal plane graphite (BPG) electrode through a simple dropping technique. Direct electrochemistry and electrocatalysis of the hemoglobin-modified electrode was investigated. The as-prepared composites showed an obvious promotion of the direct electro-transfer between hemoglobin and the electrode. A couple of well-defined and quasi-reversible Hb CV peaks can be observed in a phosphate buffer solution (pH 7.0). The separation of anodic and cathodic peak potentials is 81 mV, indicating a fast electron transfer reaction. The experimental results also clarified that the immobilized Hb retained its biological activity for the catalysis toward NO. The biosensor showed high sensitivity and fast response upon the addition of NO, under the conditions of pH 7.0, potential ‒0.82 V. The time to reach the stable-state current was less than 3 s, and the linear response range of NO was 0.72–7.92 μM, with a correlation coefficient of 0.9991.

Description: This paper presents an intelligent surveillance platform based on the usage of large numbers of inexpensive sensors designed and developed inside the European Eureka Celtic project HuSIMS. With the aim of maximizing the number of deployable units while keeping monetary and resource/bandwidth costs at a minimum, the surveillance platform is based on the usage of inexpensive visual sensors which apply efficient motion detection and tracking algorithms to transform the video signal in a set of motion parameters. In order to automate the analysis of the myriad of data streams generated by the visual sensors, the platform’s control center includes an alarm detection engine which comprises three components applying three different Artificial Intelligence strategies in parallel. These strategies are generic, domain-independent approaches which are able to operate in several domains (traffic surveillance, vandalism prevention, perimeter security, etc.). The architecture is completed with a versatile communication network which facilitates data collection from the visual sensors and alarm and video stream distribution towards the emergency teams. The resulting surveillance system is extremely suitable for its deployment in metropolitan areas, smart cities, and large facilities, mainly because cheap visual sensors and autonomous alarm detection facilitate dense sensor network deployments for wide and detailed coverage.

Description: Network simulators are useful for researching protocol performance, appraising new hardware capabilities and evaluating real application scenarios. However, these tasks can only be achieved when using accurate models and real parameters that enable the extraction of trustworthy results and conclusions. This paper presents an underwater wireless sensor network ecosystem for the ns-3 simulator. This ecosystem is composed of a new energy-harvesting model and a low-cost, low-power underwater wake-up modem model that, alongside existing models, enables the performance of accurate simulations by providing real weather and marine conditions from the location where the real application is to be deployed.

Description: An essential application of wireless sensor networks is to successfully respond to user queries. Query packet losses occur in the query dissemination due to wireless communication problems such as interference, multipath fading, packet collisions, etc. The losses of query messages at sensor nodes result in the failure of sensor nodes reporting the requested data. Hence, the reliable and successful dissemination of query messages to sensor nodes is a non-trivial problem. The target of this paper is to enable highly successful query delivery to sensor nodes by localized and energy-efficient discovery, and recovery of query losses. We adopt local and collective cooperation among sensor nodes to increase the success rate of distributed discoveries and recoveries. To enable the scalability in the operations of discoveries and recoveries, we employ a distributed name resolution mechanism at each sensor node to allow sensor nodes to self-detect the correlated queries and query losses, and then efficiently locally respond to the query losses. We prove that the collective discovery of query losses has a high impact on the success of query dissemination and reveal that scalability can be achieved by using the proposed approach. We further study the novel features of the cooperation and competition in the collective recovery at PHY and MAC layers, and show that the appropriate number of detectors can achieve optimal successful recovery rate. We evaluate the proposed approach with both mathematical analyses and computer simulations. The proposed approach enables a high rate of successful delivery of query messages and it results in short route lengths to recover from query losses. The proposed approach is scalable and operates in a fully distributed manner.

Description: The demand for Wireless Body Sensor Networks (WBSNs) is rapidly increasing due to the revolution in wearable systems demonstrated by the penetration of on-the-body sensors in hospitals, sports medicine and general health-care practices. In WBSN, the body acts as a communication channel for the propagation of electromagnetic (EM) waves, where losses are mainly due to absorption of power in the tissue. This paper shows the effects of the dielectric properties of biological tissues in the signal strength and, for the first time, relates these effects with the human body composition. After a careful analysis of results, this work proposes a reactive algorithm for power transmission to alleviate the effect of body movement and body type. This policy achieves up to 40.8% energy savings in a realistic scenario with no performance overhead.

Description: This paper presents an analysis of a golf swing to detect improper motion in the early phase of the swing. Led by the desire to achieve a consistent shot outcome, a particular golfer would (in multiple trials) prefer to perform completely identical golf swings. In reality, some deviations from the desired motion are always present due to the comprehensive nature of the swing motion. Swing motion deviations that are not detrimental to performance are acceptable. This analysis is conducted using a golfer’s leading arm kinematic data, which are obtained from a golfer wearing a motion sensor that is comprised of gyroscopes and accelerometers. Applying the principal component analysis (PCA) to the reference observations of properly performed swings, the PCA components of acceptable swing motion deviations are established. Using these components, the motion deviations in the observations of other swings are examined. Any unacceptable deviations that are detected indicate an improper swing motion. Arbitrarily long observations of an individual player’s swing sequences can be included in the analysis. The results obtained for the considered example show an improper swing motion in early phase of the swing, i.e., the first part of the backswing. An early detection method for improper swing motions that is conducted on an individual basis provides assistance for performance improvement.

Description: When it comes to measuring blade-tip clearance or blade-tip timing in turbines, reflective intensity-modulated optical fiber sensors overcome several traditional limitations of capacitive, inductive or discharging probe sensors. This paper presents the signals and results corresponding to the third stage of a multistage turbine rig, obtained from a transonic wind-tunnel test. The probe is based on a trifurcated bundle of optical fibers that is mounted on the turbine casing. To eliminate the influence of light source intensity variations and blade surface reflectivity, the sensing principle is based on the quotient of the voltages obtained from the two receiving bundle legs. A discrepancy lower than 3% with respect to a commercial sensor was observed in tip clearance measurements. Regarding tip timing measurements, the travel wave spectrum was obtained, which provides the average vibration amplitude for all blades at a particular nodal diameter. With this approach, both blade-tip timing and tip clearance measurements can be carried out simultaneously. The results obtained on the test turbine rig demonstrate the suitability and reliability of the type of sensor used, and suggest the possibility of performing these measurements in real turbines under real working conditions.

Description: Neuro-evolutive development from birth until the age of six years is a decisive factor in a child’s quality of life. Early detection of development disorders in early childhood can facilitate necessary diagnosis and/or treatment. Primary-care pediatricians play a key role in its detection as they can undertake the preventive and therapeutic actions requested to promote a child’s optimal development. However, the lack of time and little specific knowledge at primary-care avoid to applying continuous early-detection anomalies procedures. This research paper focuses on the deployment and evaluation of a smart system that enhances the screening of language disorders in primary care. Pediatricians get support to proceed with early referral of language disorders. The proposed model provides them with a decision-support tool for referral actions to trigger essential diagnostic and/or therapeutic actions for a comprehensive individual development. The research was conducted by starting from a sample of 60 cases of children with language disorders. Validation was carried out through two complementary steps: first, by including a team of seven experts from the fields of neonatology, pediatrics, neurology and language therapy, and, second, through the evaluation of 21 more previously diagnosed cases. The results obtained show that therapist positively accepted the system proposal in 18 cases (86%) and suggested system redesign for single referral to a speech therapist in three remaining cases.

Description: This article presents design issues of high-sensitive laser absorption spectroscopy systems for nitrogen oxides (NOx) detection. Examples of our systems and their investigation results are also described. The constructed systems use one of the most sensitive methods, cavity enhanced absorption spectroscopy (CEAS). They operate at different wavelength ranges using a blue—violet laser diode (410 nm) as well as quantum cascade lasers (5.27 µm and 4.53 µm). Each of them is configured as a one or two channel measurement device using, e.g., time division multiplexing and averaging. During the testing procedure, the main performance features such as detection limits and measurements uncertainties have been determined. The obtained results are 1 ppb NO2, 75 ppb NO and 45 ppb N2O. For all systems, the uncertainty of concentration measurements does not exceed a value of 13%. Some experiments with explosives are also discussed. A setup equipped with a concentrator of explosives vapours was used. The detection method is based either on the reaction of the sensors to the nitrogen oxides directly emitted by the explosives or on the reaction to the nitrogen oxides produced during thermal decomposition of explosive vapours. For TNT, PETN, RDX and HMX a detection limit better than 1 ng has been achieved.

Description: A prototype of a clip-type pulsimeter equipped with a magnetic field-sensing semiconductor Hall sensor was developed. It has a permanent magnet attached in the “Chwan” position to the center of a radial artery. The clip-type pulsimeter is composed of a hardware system measuring voltage signals. To measure spatial pulse wave velocity (SPWV), the signal from the radial artery pulsimeter and that from the photoplethysmography (PPG) were simultaneously compared. The pulse wave data from a clinical test of 39 clinical participants (male:female = 25:14) with a mean age of 24.36 (±2.35) years was analyzed. The mean SPWV, which was simultaneously measured from the radial artery pulsimeter and PPG, was 0.8 m/s. We suggest the SPWV results were higher for men than women, because of the better vascularity of terminal tissue in men. The findings of this research may be useful for developing a biomedical signal storage device for a U-health-care system.

Description: Porous silicon has been established as an excellent sensing platform for the optical detection of hazardous chemicals and biomolecular interactions such as DNA hybridization, antigen/antibody binding, and enzymatic reactions. Its porous nature provides a high surface area within a small volume, which can be easily controlled by changing the pore sizes. As the porosity and consequently the refractive index of an etched porous silicon layer depends on the electrochemial etching conditions photonic crystals composed of multilayered porous silicon films with well-resolved and narrow optical reflectivity features can easily be obtained. The prominent optical response of the photonic crystal decreases the detection limit and therefore increases the sensitivity of porous silicon sensors in comparison to sensors utilizing Fabry-Pérot based optical transduction. Development of porous silicon photonic crystal sensors which allow for the detection of analytes by the naked eye using a simple color change or the fabrication of stacked porous silicon photonic crystals showing two distinct optical features which can be utilized for the discrimination of analytes emphasize its high application potential.

Description: This study demonstrates the suitability of microfluidic structures for high throughput blood cell analysis. The microfluidic chips exploit fully integrated hydrodynamic focusing based on two different concepts: Two-stage cascade focusing and spin focusing (vortex) principle. The sample—A suspension of micro particles or blood cells—is injected into a sheath fluid streaming at a substantially higher flow rate, which assures positioning of the particles in the center of the flow channel. Particle velocities of a few m/s are achieved as required for high throughput blood cell analysis. The stability of hydrodynamic particle positioning was evaluated by measuring the pulse heights distributions of fluorescence signals from calibration beads. Quantitative assessment based on coefficient of variation for the fluorescence intensity distributions resulted in a value of about 3% determined for the micro-device exploiting cascade hydrodynamic focusing. For the spin focusing approach similar values were achieved for sample flow rates being 1.5 times lower. Our results indicate that the performances of both variants of hydrodynamic focusing suit for blood cell differentiation and counting. The potential of the micro flow cytometer is demonstrated by detecting immunologically labeled CD3 positive and CD4 positive T-lymphocytes in blood.

Description: How to describe an image accurately with the most useful information but at the same time the least useless information is a basic problem in the recognition field. In this paper, a novel and high precision feature called BG2D2LRP is proposed, accompanied with a corresponding face recognition system. The feature contains both static texture differences and dynamic contour trends. It is based on Gabor and LBP theory, operated by various kinds of transformations such as block, second derivative, direct orientation, layer and finally fusion in a particular way. Seven well-known face databases such as FRGC, AR, FERET and so on are used to evaluate the veracity and robustness of the proposed feature. A maximum improvement of 29.41% is achieved comparing with other methods. Besides, the ROC curve provides a satisfactory figure. Those experimental results strongly demonstrate the feasibility and superiority of the new feature and method.

Description: The GNSS derived Zenith Tropospheric Delay (ZTD) plays today a very critical role in meteorological study and weather forecasts, as ZTDs of thousands of GNSS stations are operationally assimilated into numerical weather prediction models. Recently, the Chinese BeiDou Navigation Satellite System (BDS) was officially announced to provide operational services around China and its neighborhood and it was demonstrated to be very promising for precise navigation and positioning. In this contribution, we concentrate on estimating ZTD using BDS observations to assess its capacity for troposphere remote sensing. A local network which is about 250 km from Beijing and comprised of six stations equipped with GPS- and BDS-capable receivers is utilized. Data from 5 to 8 November 2012 collected on the network is processed in network mode using precise orbits and in Precise Point Positioning mode using precise orbits and clocks. The precise orbits and clocks are generated from a tracking network with most of the stations in China and several stations around the world. The derived ZTDs are compared with that estimated from GPS data using the final products of the International GNSS Service (IGS). The comparison shows that the bias and the standard deviation of the ZTD differences are about 2 mm and 5 mm, respectively, which are very close to the differences of GPS ZTD estimated using different software packages.

Description: Fabric defect inspection is necessary and essential for quality control in the textile industry. Traditionally, fabric inspection to assure textile quality is done by humans, however, in the past years, researchers have paid attention to PC-based automatic inspection systems to improve the detection efficiency. This paper proposes a novel automatic inspection scheme for the warp knitting machine using smart visual sensors. The proposed system consists of multiple smart visual sensors and a controller. Each sensor can scan 800 mm width of web, and can work independently. The following are considered in dealing with broken-end defects caused by a single yarn: first, a smart visual sensor is composed of a powerful DSP processor and a 2-megapixel high definition image sensor. Second, a wavelet transform is used to decompose fabric images, and an improved direct thresholding method based on high frequency coefficients is proposed. Third, a proper template is chosen in a mathematical morphology filter to remove noise. Fourth, a defect detection algorithm is optimized to meet real-time demands. The proposed scheme has been running for six months on a warp knitting machine in a textile factory. The actual operation shows that the system is effective, and its detection rate reaches 98%.

Description: The one-dimensional (1D) power law velocity distribution, commonly used for computing velocities in open channel flow, has been derived empirically. However, a multitude of problems, such as scour around bridge piers, cutoffs and diversions, pollutant dispersion, and so on, require the velocity distribution in two dimensions. This paper employs the Shannon entropy theory for deriving the power law velocity distribution in two-dimensions (2D). The development encompasses the rectangular domain, but can be extended to any arbitrary domain, including a trapezoidal domain. The derived methodology requires only a few parameters and the good agreement is confirmed by comparing the velocity values calculated using the proposed methodology with values derived from both the 1D power law model and a logarithmic velocity distribution available in the literature.

Description: Studies of learning algorithms typically concentrate on situations where potentially ever growing training sample is available. Yet, there can be situations (e.g., detection of differentially expressed genes on unreplicated data or estimation of time delay in non-stationary gravitationally lensed photon streams) where only extremely small samples can be used in order to perform an inference. On unreplicated data, the inference has to be performed on the smallest sample possible—sample of size 1. We study whether anything useful can be learnt in such extreme situations by concentrating on a Bayesian approach that can account for possible prior information on expected counts. We perform a detailed information theoretic study of such Bayesian estimation and quantify the effect of Bayesian averaging on its first two moments. Finally, to analyze potential benefits of the Bayesian approach, we also consider Maximum Likelihood (ML) estimation as a baseline approach. We show both theoretically and empirically that the Bayesian model averaging can be potentially beneficial.

Description: Molecular dynamics simulations are used to study the evaporation of water droplets containing either dissolved LiCl, NaCl or KCl salt in a gaseous surrounding (nitrogen) with a constant high temperature of 600 K. The initial droplet has 298 K temperature and contains 1,120 water molecules, 0, 40, 80 or 120 salt molecules. The effects of the salt type and concentration on the evaporation rate are examined. Three stages with different evaporation rates are observed for all cases. In the initial stage of evaporation, the droplet evaporates slowly due to low droplet temperature and high evaporation latent heat for water, and pure water and aqueous solution have almost the same evaporation rates. In the second stage, evaporation rate is increased significantly, and evaporation is somewhat slower for the aqueous salt-containing droplet than the pure water droplet due to the attracted ion-water interaction and hydration effect. The Li+-water has the strongest interaction and hydration effect, so LiCl aqueous droplets evaporate the slowest, then NaCl and KCl. Higher salt concentration also enhances the ion-water interaction and hydration effect, and hence corresponds to a slower evaporation. In the last stage of evaporation, only a small amount of water molecules are left in the droplet, leading to a significant increase in ion-water interactions, so that the evaporation becomes slower compared to that in the second stage.

Description: Bell-shaped vibratory angular rate gyro (abbreviated as BVG) is a new type Coriolis vibratory gyro that was inspired by Chinese traditional clocks. The resonator fuses based on a variable thickness axisymmetric multicurved surface shell. Its characteristics can directly influence the performance of BVG. The BVG structure not only has capabilities of bearing high overload, high impact and, compared with the tuning fork, vibrating beam, shell and a comb structure, but also a higher frequency to overcome the influence of the disturbance of the exterior environment than the same sized hemispherical resonator gyroscope (HRG) and the traditional cylinder vibratory gyroscope. It can be widely applied in high dynamic low precision angular rate measurement occasions. The main work is as follows: the issue mainly analyzes the structure and basic principle, and investigates the bell-shaped resonator’s mathematical model. The reasonable structural parameters are obtained from finite element analysis and an intelligent platform. Using the current solid vibration gyro theory analyzes the structural characteristics and principles of BVG. The bell-shaped resonator is simplified as a paraboloid of the revolution mechanical model, which has a fixed closed end and a free opened end. It obtains the natural frequency and vibration modes based on the theory of elasticity. The structural parameters are obtained from the orthogonal method by the research on the structural parameters of the resonator analysis. It obtains the modal analysis, stress analysis and impact analysis with the chosen parameters. Finally, using the turntable experiment verifies the gyro effect of the BVG.

Description: Sensor technology has matured enough to be used in any type of environment. The appearance of new physical sensors has increased the range of environmental parameters for gathering data. Because of the huge amount of unexploited resources in the ocean environment, there is a need of new research in the field of sensors and sensor networks. This special issue is focused on collecting recent advances on underwater sensors and underwater sensor networks in order to measure, monitor, surveillance of and control of underwater environments. On the one hand, from the sensor node perspective, we will see works related with the deployment of physical sensors, development of sensor nodes and transceivers for sensor nodes, sensor measurement analysis and several issues such as layer 1 and 2 protocols for underwater communication and sensor localization and positioning systems. On the other hand, from the sensor network perspective, we will see several architectures and protocols for underwater environments and analysis concerning sensor network measurements. Both sides will provide us a complete view of last scientific advances in this research field.

Description: A methodology for the determination of the solid-fluid contact angle, to be employed within molecular dynamics (MD) simulations, is developed and systematically applied. The calculation of the contact angle of a fluid drop on a given surface, averaged over an equilibrated MD trajectory, is divided in three main steps: (i) the determination of the fluid molecules that constitute the interface, (ii) the treatment of the interfacial molecules as a point cloud data set to define a geometric surface, using surface meshing techniques to compute the surface normals from the mesh, (iii) the collection and averaging of the interface normals collected from the post-processing of the MD trajectory. The average vector thus found is used to calculate the Cassie contact angle (i.e., the arccosine of the averaged normal z-component). As an example we explore the effect of the size of a drop of water on the observed solid-fluid contact angle. A single coarse-grained bead representing two water molecules and parameterized using the SAFT-γ Mie equation of state (EoS) is employed, meanwhile the solid surfaces are mimicked using integrated potentials. The contact angle is seen to be a strong function of the system size for small nano-droplets. The thermodynamic limit, corresponding to the infinite size (macroscopic) drop is only truly recovered when using an excess of half a million water coarse-grained beads and/or a drop radius of over 26 nm.

Description: The correlation distance quantifies the statistical independence of two classical or quantum systems, via the distance from their joint state to the product of the marginal states. Tight lower bounds are given for the mutual information between pairs of two-valued classical variables and quantum qubits, in terms of the corresponding classical and quantum correlation distances. These bounds are stronger than the Pinsker inequality (and refinements thereof) for relative entropy. The classical lower bound may be used to quantify properties of statistical models that violate Bell inequalities. Partially entangled qubits can have lower mutual information than can any two-valued classical variables having the same correlation distance. The qubit correlation distance also provides a direct entanglement criterion, related to the spin covariance matrix. Connections of results with classically-correlated quantum states are briefly discussed.

Description: We consider the learning coefficients in learning theory and give two new methods for obtaining these coefficients in a homogeneous case: a method for finding a deepest singular point and a method to add variables. In application to Vandermonde matrix-type singularities, we show that these methods are effective. The learning coefficient of the generalization error in Bayesian estimation serves to measure the learning efficiency in singular learning models. Mathematically, the learning coefficient corresponds to a real log canonical threshold of singularities for the Kullback functions (relative entropy) in learning theory.

Description: In this paper we present a new method for hand gesture recognition based on an RGB-D sensor. The proposed approach takes advantage of depth information to cope with the most common problems of traditional video-based hand segmentation methods: cluttered backgrounds and occlusions. The algorithm also uses colour and semantic information to accurately identify any number of hands present in the image. Ten different static hand gestures are recognised, including all different combinations of spread fingers. Additionally, movements of an open hand are followed and 6 dynamic gestures are identified. The main advantage of our approach is the freedom of the user’s hands to be at any position of the image without the need of wearing any specific clothing or additional devices. Besides, the whole method can be executed without any initial training or calibration. Experiments carried out with different users and in different environments prove the accuracy and robustness of the method which, additionally, can be run in real-time.

Description: In this paper, we investigate the combination synchronization of three nonlinear complex hyperchaotic systems: the complex hyperchaotic Lorenz system, the complex hyperchaotic Chen system and the complex hyperchaotic L¨u system. Based on the Lyapunov stability theory, corresponding controllers to achieve combination synchronization among three identical or different nonlinear complex hyperchaotic systems are derived, respectively. Numerical simulations are presented to demonstrate the validity and feasibility of the theoretical analysis.

Description: Wireless Sensor Networks (WSNs) are a technology that is becoming very popular for many applications, and environmental monitoring is one of its most important application areas. This technology solves the lack of flexibility of wired sensor installations and, at the same time, reduces the deployment costs. To demonstrate the advantages of WSN technology, for the last five years we have been deploying some prototypes in the Doñana Biological Reserve, which is an important protected area in Southern Spain. These prototypes not only evaluate the technology, but also solve some of the monitoring problems that have been raised by biologists working in Doñana. This paper presents a review of the work that has been developed during these five years. Here, we demonstrate the enormous potential of using machine learning in wireless sensor networks for environmental and animal monitoring because this approach increases the amount of useful information and reduces the effort that is required by biologists in an environmental monitoring task.

Description: Existing algorithms for learning Boolean networks (BNs) have time complexities of at least O(N · n0:7(k+1)), where n is the number of variables, N is the number of samples and k is the number of inputs in Boolean functions. Some recent studies propose more efficient methods with O(N · n2) time complexities. However, these methods can only be used to learn monotonic BNs, and their performances are not satisfactory when the sample size is small. In this paper, we mathematically prove that OR/ANDBNs, where the variables are related with logical OR/AND operations, can be found with the time complexity of O(k·(N+ logn)·n2), if there are enough noiseless training samples randomly generated from a uniform distribution. We also demonstrate that our method can successfully learn most BNs, whose variables are not related with exclusive OR and Boolean equality operations, with the same order of time complexity for learning OR/AND BNs, indicating our method has good efficiency for learning general BNs other than monotonic BNs. When the datasets are noisy, our method can still successfully identify most BNs with the same efficiency. When compared with two existing methods with the same settings, our method achieves a better comprehensive performance than both of them, especially for small training sample sizes. More importantly, our method can be used to learn all BNs. However, of the two methods that are compared, one can only be used to learn monotonic BNs, and the other one has a much worse time complexity than our method. In conclusion, our results demonstrate that Boolean networks can be learned with improved time complexities.

Description: Microstructure and phase composition of a CrMo0.5NbTa0.5TiZr high entropy alloy were studied in the as-solidified and heat treated conditions. In the as-solidified condition, the alloy consisted of two disordered BCC phases and an ordered cubic Laves phase. The BCC1 phase solidified in the form of dendrites enriched with Mo, Ta and Nb, and its volume fraction was 42%. The BCC2 and Laves phases solidified by the eutectic-type reaction, and their volume fractions were 27% and 31%, respectively. The BCC2 phase was enriched with Ti and Zr and the Laves phase was heavily enriched with Cr. After hot isostatic pressing at 1450 °C for 3 h, the BCC1 dendrites coagulated into round-shaped particles and their volume fraction increased to 67%. The volume fractions of the BCC2 and Laves phases decreased to 16% and 17%, respectively. After subsequent annealing at 1000 °C for 100 h, submicron-sized Laves particles precipitated inside the BCC1 phase, and the alloy consisted of 52% BCC1, 16% BCC2 and 32% Laves phases. Solidification and phase equilibrium simulations were conducted for the CrMo0.5NbTa0.5TiZr alloy using a thermodynamic database developed by CompuTherm LLC. Some discrepancies were found between the calculated and experimental results and the reasons for these discrepancies were discussed.

Description: The errors of low-cost inertial sensors, especially Micro-Electro Mechanical Systems (MEMS) ones, are highly dependent on environmental conditions such as the temperature. Thus, there is a need for the development of accurate and reliable thermal compensation models to reduce the impact of such thermal drift of the sensors. Since the conventional thermal calibration methods are typically time-consuming and costly, an efficient thermal calibration method to investigate the thermal drift of a full set of gyroscope and accelerometer errors (i.e., biases, scale factor errors and non-orthogonalities) over the entire temperature range in a few hours is proposed. The proposed method uses the idea of the Ramp method, which removes the time-consuming process of stabilizing the sensor temperature, and addresses its inherent problems with several improvements. We change the temperature linearly for a complete cycle and take a balanced strategy by making comprehensive use of the sensor measurements during both heating and cooling processes. Besides, an efficient 8-step rotate-and-static scheme is designed to further improve the calibration accuracy and efficiency. Real calibration tests showed that the proposed method is suitable for low-grade IMUs and for both lab and factory calibration due to its efficiency and sufficient accuracy.