Infrared attenuated total reflection (ATR) spectroscopy is a common laboratory technique for the analysis of highly absorbing liquids and solids. However, in a process environment, maintaining a sufficient sample exchange and cleaning of the sensitive surface of the element is a crucial issue. An important industrial application is the measurement of isocyanate concentrations. Isocyanates are necessary for the fabrication of polyurethane materials and are among the chemicals with the highest production volume worldwide. For process applications, narrowband photometers or MEMS spectrometers are more appropriate than the use of bulky FTIR instruments frequently encountered in a laboratory environment. Toluene diisocyanate (TDI) and hexamethylene diisocyanate (HDI) concentrations are measured with a planar ATR photometer setup. Using a miniature Fabry–Perot interferometer (FPI), trace concentrations below 100 ppm (m/m) are detected. By employing an ATR element of the cylindrical shape, sensors can be realized with a smooth surface ideally suited for an automatic cleaning system in a process environment. A laboratory setup with sapphire tubes as ATR elements for incorporation in a liquid flow system is described. Reflection and transmission configurations were investigated. Measurements with acetonitrile as a less toxic substitute showed that with cylindrical ATR sensors’ detection limits for isocyanate concentrations below 100 ppm (m/m) are feasible. Full article

Ultra-wideband (UWB) radar has become a critical remote-sensing tool for non-contact vital sign detection such as emergency rescues, securities, and biomedicines. Theoretically, the magnitude of the received reflected signal is dependent on the central frequency of mono-pulse waveform used as the transmitted signal. The research is based on the hypothesis that the stronger the received reflected signals, the greater the detectability of life signals. In this paper, we derive a new formula to compute the optimal central frequency to obtain as maximum received reflect signal as possible over the frequency up to the lower range of Ka-band. The proposed formula can be applicable in the optimization of hardware for UWB life detection and non-contact monitoring of vital signs. Furthermore, the vital sign detection results obtained by the UWB radar over a range of central frequency have been compared to those of the former continuous (CW) radar to provide additional information regarding the advantages and disadvantages of each radar. Full article

Cultural heritage objects are affected by a wide range of factors causing their deterioration and decay over time such as ground deformations, changes in hydrographic conditions, vibrations or excess of moisture, which can cause scratches and cracks formation in the case of historic buildings. The electromagnetic spectroscopy has been widely used for non-destructive structural health monitoring of concrete structures. However, the limitation of this technology is a lack of geolocalisation in the space for multispectral architectural documentation. The aim of this study is to examine different geolocalisation methods in order to determine the position of the sensor system, which will then allow to georeference the results of measurements performed by this device and apply corrections to the sensor response, which is a crucial element required for further data processing related to the object structure and its features. The classical surveying, terrestrial laser scanning (TLS), and Structure-from-Motion (SfM) photogrammetry methods were used in this investigation at three test sites. The methods were reviewed and investigated. The results indicated that TLS technique should be applied for simple structures and plain textures, while the SfM technique should be used for marble-based and other translucent or semi-translucent structures in order to achieve the highest accuracy for geolocalisation of the proposed sensor system. Full article

Image binarization is one of the key operations decreasing the amount of information used in further analysis of image data, significantly influencing the final results. Although in some applications, where well illuminated images may be easily captured, ensuring a high contrast, even a simple global thresholding may be sufficient, there are some more challenging solutions, e.g., based on the analysis of natural images or assuming the presence of some quality degradations, such as in historical document images. Considering the variety of image binarization methods, as well as their different applications and types of images, one cannot expect a single universal thresholding method that would be the best solution for all images. Nevertheless, since one of the most common operations preceded by the binarization is the Optical Character Recognition (OCR), which may also be applied for non-uniformly illuminated images captured by camera sensors mounted in mobile phones, the development of even better binarization methods in view of the maximization of the OCR accuracy is still expected. Therefore, in this paper, the idea of the use of robust combined measures is presented, making it possible to bring together the advantages of various methods, including some recently proposed approaches based on entropy filtering and a multi-layered stack of regions. The experimental results, obtained for a dataset of 176 non-uniformly illuminated document images, referred to as the WEZUT OCR Dataset, confirm the validity and usefulness of the proposed approach, leading to a significant increase of the recognition accuracy. Full article

In the traditional electronic health record (EHR) management system, each medical service center manages their own health records, respectively, which are difficult to share on the different medical platforms. Recently, blockchain technology is one of the popular alternatives to enable medical service centers based on different platforms to share EHRs. However, it is hard to store whole EHR data in blockchain because of the size and the price of blockchain. To resolve this problem, cloud computing is considered as a promising solution. Cloud computing offers advantageous properties such as storage availability and scalability. Unfortunately, the EHR system with cloud computing can be vulnerable to various attacks because the sensitive data is sent over a public channel. We propose the secure protocol for cloud-assisted EHR system using blockchain. In the proposed scheme, blockchain technology is used to provide data integrity and access control using log transactions and the cloud server stores and manages the patient’s EHRs to provide secure storage resources. We use an elliptic curve cryptosystems (ECC) to provide secure health data sharing with cloud computing. We demonstrate that the proposed EHR system can prevent various attacks by using informal security analysis and automated validation of internet security protocols and applications (AVISPA) simulation. Furthermore, we prove that the proposed EHR system provides secure mutual authentication using BAN logic analysis. We then compare the computation overhead, communication overhead, and security properties with existing schemes. Consequently, the proposed EHR system is suitable for the practical healthcare system considering security and efficiency. Full article

The large amount of sensors in modern electrical networks poses a serious challenge in the data processing side. For many years, spectral analysis has been one of the most used approaches to extract physically meaningful information from a sea of data. Fourier Transform (FT) and Wavelet Transform (WT) are by far the most employed tools in this analysis. In this paper we explore the alternative use of Hilbert–Huang Transform (HHT) for electricity demand spectral representation. A sequence of hourly consumptions, spanning 40 months of electrical demand in Spain, has been used as dataset. First, by Empirical Mode Decomposition (EMD), the sequence has been time-represented as an ensemble of 13 Intrinsic Mode Functions (IMFs). Later on, by applying Hilbert Transform (HT) to every IMF, an HHT spectrum has been obtained. Results show smoother spectra with more defined shapes and an excellent frequency resolution. EMD also fosters a deeper analysis of abnormal electricity demand at different timescales. Additionally, EMD permits information compression, which becomes very significant for lossless sequence representation. A 35% reduction has been obtained for the electricity demand sequence. On the negative side, HHT demands more computer resources than conventional spectral analysis techniques. Full article

Deep-sea ecological monitoring is increasingly recognized as indispensable for the comprehension of the largest biome on Earth, but at the same time it is subjected to growing human impacts for the exploitation of biotic and abiotic resources. Here, we present the Naples Ecological REsearch (NEREA) stand-alone observatory concept (NEREA-fix), an integrated observatory with a modular, adaptive structure, characterized by a multiparametric video-platform to be deployed in the Dohrn canyon (Gulf of Naples, Tyrrhenian Sea) at ca. 650 m depth. The observatory integrates a seabed platform with optoacoustic and oceanographic/geochemical sensors connected to a surface transmission buoy, plus a mooring line (also equipped with depth-staged environmental sensors). This reinforced high-frequency and long-lasting ecological monitoring will integrate the historical data conducted over 40 years for the Long-Term Ecological Research (LTER) at the station “Mare Chiara”, and ongoing vessel-assisted plankton (and future environmental DNA-eDNA) sampling. NEREA aims at expanding the observational capacity in a key area of the Mediterranean Sea, representing a first step towards the establishment of a bentho-pelagic network to enforce an end-to-end transdisciplinary approach for the monitoring of marine ecosystems across a wide range of animal sizes (from bacteria to megafauna). Full article

The present paper aims to investigate the influence of perforated membrane geometry on the performance of biosensors. For this purpose, a 2-D axisymmetric model of an amperometric biosensor is analyzed. The governing equations describing the reaction-diffusion equations containing a nonlinear term related to the Michaelis–Menten kinetics of the enzymatic reaction are introduced. The partial differential governing equations, along with the boundary conditions, are first non-dimensionalized by using appropriate dimensionless variables and then solved in a non-uniform unstructured grid by employing the Galerkin Finite Element Method. To examine the impact of the hole-geometry of the perforated membrane, seven different geometries—including cylindrical, upward circular cone, downward circular cone, upward paraboloid, downward paraboloid, upward concave paraboloid, and downward concave paraboloid—are studied. Moreover, the effects of the perforation level of the perforated membrane, the filling level of the enzyme on the transient and steady-state current of the biosensor, and the half-time response are presented. The results of the simulations show that the transient and steady-state current of the biosensor are affected by the geometry dramatically. Thus, the sensitivity of the biosensor can be influenced by different hole-geometries. The minimum and maximum output current can be obtained from the cylindrical and upward concave paraboloid holes. On the other hand, the least half-time response of the biosensor can be obtained in the cylindrical geometry. Full article

Bioluminescence resonance energy transfer (BRET) is the non-radiative transfer of energy from a bioluminescent protein donor to a fluorophore acceptor. It shares all the formalism of Förster resonance energy transfer (FRET) but differs in one key aspect: that the excited donor here is produced by biochemical means and not by an external illumination. Often the choice of BRET source is the bioluminescent protein Renilla luciferase, which catalyzes the oxidation of a substrate, typically coelenterazine, producing an oxidized product in its electronic excited state that, in turn, couples with a proximal fluorophore resulting in a fluorescence emission from the acceptor. The acceptors pertinent to this discussion are semiconductor quantum dots (QDs), which offer some unrivalled photophysical properties. Amongst other advantages, the QD’s large Stokes shift is particularly advantageous as it allows easy and accurate deconstruction of acceptor signal, which is difficult to attain using organic dyes or fluorescent proteins. QD-BRET systems are gaining popularity in non-invasive bioimaging and as probes for biosensing as they don’t require external optical illumination, which dramatically improves the signal-to-noise ratio by avoiding background auto-fluorescence. Despite the additional advantages such systems offer, there are challenges lying ahead that need to be addressed before they are utilized for translational types of research. Full article

This study presents the design and fabrication of a flexible tactile sensor printed on a cellulose paper substrate using a carbon black (CB) – filled polyvinyl alcohol (PVA) polymer matrix as ink material. In the design, electrodes are obtained by screen printing of CB/PVA composite on dielectric cellulose paper. The screen-printing method is preferred for fabrication because of its simplicity and low manufacturing cost. The tactile sensor is formed by overlapping two ink-printed sheets. Electrical properties are investigated under compressive and tensile strains. The results indicate that the tactile sensor configuration and materials can be used for piezoresistive, capacitive, and also impedance sensors. The same tactile sensor structure is also examined using a commercial carbon-based ink for performance comparison. The comparative study indicates that CB/PVA ink screen-printed on paper demonstrates superior sensitivity for capacitive sensing with low hysteresis, as well as low response and recovery times. The piezoresistive-sensing properties of CB/PVA on cellulose paper show a gauge factor (GF) of 10.68, which is also very promising when conventional metal strain gauges are considered. CB/PVA screen-printed on cellulose paper features impedance-sensing properties and is also sensitive to the measurement frequency. Therefore, the response type of the sensor can be altered with the frequency. Full article

Semantic segmentation of street view images is an important step in scene understanding for autonomous vehicle systems. Recent works have made significant progress in pixel-level labeling using Fully Convolutional Network (FCN) framework and local multi-scale context information. Rich global context information is also essential in the segmentation process. However, a systematic way to utilize both global and local contextual information in a single network has not been fully investigated. In this paper, we propose a global-and-local network architecture (GLNet) which incorporates global spatial information and dense local multi-scale context information to model the relationship between objects in a scene, thus reducing segmentation errors. A channel attention module is designed to further refine the segmentation results using low-level features from the feature map. Experimental results demonstrate that our proposed GLNet achieves 80.8% test accuracy on the Cityscapes test dataset, comparing favorably with existing state-of-the-art methods. Full article

The conventional temperature drift error (TDE) compensation model cannot decouple temperature dependence of Si-based materials because temperature correlated quantities (TCQ) have not been obtained comprehensively, and Micro-Electro-Mechanical System gyros’ (MEMS-gyros’) environmental adaptability is reduced in diverse, complicated conditions. The study presents modification of TDE compensation model of MEMS-gyros based on microstructure thermal effect analysis (MTEA). First, Si-based materials’ temperature dependence was studied in microstructure with thermal expansion effect and TCQ that determines the structural deformation were extracted to modify the conventional model, including temperature variation and its square. Second, a precise TDE test method was formed by analyzing heat conduction process between MEMS-gyros and thermal chamber, and temperature experiments were designed and conducted. Third, the modified model’s parameters were identified based on radical basis function artificial neural network (RBF ANN) and its performance was evaluated. Last, the conventional and modified models were compared in performance. The experimental results show MEMS-gyros’ bias stability was up to 10% of the conventional model, the temperature dependence of Si-based materials was decoupled better by the modified one and the environmental adaptability of MEMS-gyros was improved to expand their application in diverse complicated conditions. Full article

Existing public domain multi-modal datasets for human action recognition only include actions of interest that have already been segmented from action streams. These datasets cannot be used to study a more realistic action recognition scenario where actions of interest occur randomly and continuously among actions of non-interest or no actions. It is more challenging to recognize actions of interest in continuous action streams since the starts and ends of these actions are not known and need to be determined in an on-the-fly manner. Furthermore, there exists no public domain multi-modal dataset in which video and inertial data are captured simultaneously for continuous action streams. The main objective of this paper is to describe a dataset that is collected and made publicly available, named Continuous Multimodal Human Action Dataset (C-MHAD), in which video and inertial data stream are captured simultaneously in a continuous way. This dataset is then used in an example recognition technique and the results obtained indicate that the fusion of these two sensing modalities increases the F1 scores compared to using each sensing modality individually. Full article

Transforming individual carbon nanotubes (CNTs) into bulk form is necessary for the utilization of the extraordinary properties of CNTs in sensor applications. Individual CNTs are randomly arranged when transformed into the bulk structure in the form of buckypaper. The random arrangement has many pores among individual CNTs, which can be treated as gaps or defects contributing to the degradation of CNT properties in the bulk form. A novel technique of filling these gaps is successfully developed in this study and termed as a gap-filling technique (GFT). The GFT is implemented on SWCNT-based buckypaper in which the pores are filled through small-size MWCNTs, resulting in a ~45.9% improvement in packing density. The GFT is validated through the analysis of packing density along with characterization and surface morphological study of buckypaper using Raman spectrum, particle size analysis, scanning electron microscopy, atomic force microscopy and optical microscopy. The sensor characteristics parameters of buckypaper are investigated using a dynamic mechanical analyzer attached with a digital multimeter. The percentage improvement in the electrical conductivity, tensile gauge factor, tensile strength and failure strain of a GFT-implemented buckypaper sensor are calculated as 4.11 ± 0.61, 44.81 ± 1.72, 49.82 ± 8.21 and 113.36 ± 28.74, respectively. Full article

In recent years, research concerning autonomous driving has gained momentum to enhance road safety and traffic efficiency. Relevant concepts are being applied to the fields of perception, planning, and control of automated vehicles to leverage the advantages offered by the vehicle-to-everything (V2X) communication technology. This paper presents a V2X communication-aided autonomous driving system for vehicles. It is comprised of three subsystems: beyond line-of-sight (BLOS) perception, extended planning, and control. Specifically, the BLOS perception subsystem facilitates unlimited LOS environmental perception through data fusion between local perception using on-board sensors and communication perception via V2X. In the extended planning subsystem, various algorithms are presented regarding the route, velocity, and behavior planning to reflect real-time traffic information obtained utilizing V2X communication. To verify the results, the proposed system was integrated into a full-scale vehicle that participated in the 2019 Hyundai Autonomous Vehicle Competition held in K-city with the V2X infrastructure. Using the proposed system, the authors demonstrated successful completion of all assigned real-life-based missions, including emergency braking caused by a jaywalker, detouring around a construction site ahead, complying with traffic signals, collision avoidance, and yielding the ego-lane for an emergency vehicle. The findings of this study demonstrated the possibility of several potential applications of V2X communication with regard to autonomous driving systems. Full article