bluuebunny/crossref_metadata_2025 huggingface dataset:
Graphene Oxide and Oxidized Carbon Black as Catalyst for Crosslinking of Phenolic Resins
Authors: Acocella Maria Rosaria , Vittore Aniello , Maggio Mario , Guerra Gaetano , Giannini Luca , Tadiello Luciano
Published: August 2019

Influence of different graphite-based nanofillers on crosslinking reaction of resorcinol, as induced by hexa(methoxymethyl)melamine, is studied. Curing reactions leading from low molecular mass compounds to crosslinked insoluble networks are studied by indirect methods based on Differential Scanning Calorimetry. Reported results show a catalytic activity of graphene oxide (eGO) on this reaction, comparable to that one already described in the literature for curing of benzoxazine. For instance, for an eGO content of 2 wt %, the exothermic crosslinking DSC peak (upon heating at 10 °C/min) shifted 6 °C. More relevantly, oxidized carbon black (oCB) is much more effective as catalyst of the considered curing reaction. In fact, for an oCB content of 2 wt %, the crosslinking DSC peak can be shifted more than 30 °C and a nearly complete crosslinking is already achieved by thermal treatment at 120 °C. The possible origin of the higher catalytic activity of oCB with respect to eGO is discussed.
Functionalization of Partially Bio-Based Poly(Ethylene Terephthalate) by Blending with Fully Bio-Based Poly(Amide) 10,10 and a Glycidyl Methacrylate-Based Compatibilizer
Authors: Jorda Maria , Montava-Jorda Sergi , Balart Rafael , Lascano Diego , Montanes Nestor , Quiles-Carrillo Luis
Published: August 2019

This work shows the potential of binary blends composed of partially bio-based poly(ethyelene terephthalate) (bioPET) and fully bio-based poly(amide) 10,10 (bioPA1010). These blends are manufactured by extrusion and subsequent injection moulding and characterized in terms of mechanical, thermal and thermomechanical properties. To overcome or minimize the immiscibility, a glycidyl methacrylate copolymer, namely poly(styrene-ran-glycidyl methacrylate) (PS-GMA; Xibond™ 920) was used. The addition of 30 wt % bioPA provides increased renewable content up to 50 wt %, but the most interesting aspect is that bioPA contributes to improved toughness and other ductile properties such as elongation at yield. The morphology study revealed a typical immiscible droplet-like structure and the effectiveness of the PS-GMA copolymer was assessed by field emission scanning electron microcopy (FESEM) with a clear decrease in the droplet size due to compatibilization. It is possible to conclude that bioPA1010 can positively contribute to reduce the intrinsic stiffness of bioPET and, in addition, it increases the renewable content of the developed materials.
Impact of Ornamental Vegetation Type and Different Substrate Layers on Pollutant Removal in Constructed Wetland Mesocosms Treating Rural Community Wastewater
Authors: Zamora Sergio , Sandoval Luis , Marín-Muñíz J. Luis , Fernández-Lambert Gregorio , Hernández-Orduña M. Graciela
Published: August 2019

Improving water quality is a relevant environmental aspect, and using constructed wetlands (CWs) is a sustainable option for this; both porous material filled cells and plants that collectively remove contaminants must be readily available and inexpensive. This study evaluated CWs and their functionality by comparing two ornamental plants (Spathiphyllum wallisii and Hedychium coronarium) planted in experimental mesocosm units filled with layers of porous river rock, tepezil, and soil, or in mesocosms with layers of porous river rock, and tepezil, without the presence of soil. The findings during the experiments (180 days), showed that the removal of pollutants (chemical oxygen demand (COD), total solids suspended (TSS), nitrogen as ammonium (N-NH4), as nitrate (N-NO3), and phosphate (P-PO4) was 20–50% higher in mesocosms with vegetation that in the absence of this, and those mesocosms with the soil layer between 33–45% favored removal of P-PO4. Differences regarding of vegetation removal were only observed for N-NH4, being 25–45% higher in CWs with H. coronarium, compared with S. wallisii. Both species are suitable for using in CWs, for its functionality as phytoremediation, and aesthetic advantages could generate interest for wastewater treatment in rural communities, parks, schools or in domiciliary levels like floral flower boxes in the backyard. The study also revealed that a soil layer in CWs is necessary to increase the removal of P-PO4, an ion hardly eliminated in water treatment.
Land Resources Evaluation for Damage Compensation to Indigenous Peoples in the Arctic (Case-Study of Anabar Region in Yakutia)
Authors: Nosov Sergey I. , Bondarev Boris E. , Gladkov Andrey A. , Gassiy Violetta
Published: August 2019

The compensation for losses caused to the indigenous peoples in Arctic Russia due to the industrial development of their traditional lands is an urgent question whose resolution requires development of new mechanisms and tools. The losses caused to indigenous traditional lands are part of the damage caused to the natural environment, their culture and livelihood. In the Russian Federation cultural impact assessment is a rather new tool aiming to protect indigenous peoples’ rights to lands. In this paper the authors show the applied side of the cultural assessment that is used to improve the methodology of the calculation of losses adopted by ministry of regional development in Russia in 2009. This methodology is based on the resource disposition and evaluation of traditional lands. Accordingly, compensation payments are calculated as the sum of the losses in traditional economic activities such as: reindeer herding, hunting, fishing and gathering. Such compensation is considered by authors as the elements of a benefit-sharing system. In practice, this methodology has been tested at industrial projects on alluvial diamonds in Yakutia. In this paper we look at the Polovinnya project case-study which deals with indigenous peoples of Dolgans and Evenks and argues that such a justified, understandable methodology both for indigenous peoples and subsoil user could reduce to a minimum the conflict of interests.
Morais Ultramafic Complex: A Survey towards Nickel Phytomining
Authors: Alves Ana R. A. , Silva Eduardo F. , Novo Luís A. B.
Published: August 2019

Ultramafic areas are critical for nickel (Ni) phytomining due to the high concentration of this element in their soils and the number of hyperaccumulators they harbor. The aim of the present study was to evaluate the potential of the Morais massif, an ultramafic area in Portugal, for phytomining using the hyperaccumulator species Alyssum serpyllifolium subsp. lusitanicum. Soil samples and A. serpyllifolium specimens were collected in four locations of the Morais massif. After determination of Ni concentrations in the samples, the results show that soil pseudo-total Ni concentrations in sites number 1 and 2 are significantly higher than in the soil samples collected in the other two locations, with 1918 and 2092 mg kg−1, respectively. Nickel accumulation is significantly greater in the aerial parts of plants collected at sites 1, 2, and 4, presenting Ni harvestable amount means of 88.36, 93.80, and 95.56 mg per plant, respectively. These results suggest that the sites with highest potential for phytomining are sites 1, 2, and 4. A nickel agromining system in these locations could represent an additional source of income to local farmers, since ultramafic soils have low productivity for agriculture and crop production.
Photogrammetric Solution for Analysis of Out-Of-Plane Movements of a Masonry Structure in a Large-Scale Laboratory Experiment
Authors: Sánchez-Aparicio Luis Javier , Herrero-Huerta Mónica , Esposito Rita , Roel Schipper Hugo , González-Aguilera Diego
Published: August 2019

This paper proposes a photogrammetric procedure able to determine out-of-plane movements experienced by a masonry structure subjected to a quasi-static cyclic test. The method tracks the movement of circular targets by means of a coarse-to-fine strategy. These targets were captured by means of a photogrammetric network, made up of four cameras optimized following the precepts of a zero-, first-, and second-order design. The centroid of each circular target was accurately detected for each image using the Hough transform, a sub-pixel edge detector based on the partial area effect, and a non-linear square optimization strategy. The three-dimensional (3D) coordinates of these targets were then computed through a photogrammetric bundle adjustment considering a self-calibration model of the camera. To validate the photogrammetric method, measurements were carried out in parallel to an ongoing test on a full-scale two-story unreinforced masonry structure (5.4 × 5.2 × 5.4-m) monitored with more than 200 contact sensors. The results provided by the contact sensors during one of the load phases were compared with those obtained by the proposed approach. According to this accuracy assessment, the method was able to determine the out-of-plane displacement during the quasi-static cyclic test with a sub-pixel accuracy of 0.58.
An Improved Generalized Chirp Scaling Algorithm Based on Lagrange Inversion Theorem for High-Resolution Low Frequency Synthetic Aperture Radar Imaging
Authors: Chen Xing , Yi Tianzhu , He Feng , He Zhihua , Dong Zhen
Published: August 2019

The high-resolution low frequency synthetic aperture radar (SAR) has serious range-azimuth phase coupling due to the large bandwidth and long integration time. High-resolution SAR processing methods are necessary for focusing the raw data of such radar. The generalized chirp scaling algorithm (GCSA) is generally accepted as an attractive solution to focus SAR systems with low frequency, large bandwidth and wide beam bandwidth. However, as the bandwidth and/or beamwidth increase, the serious phase coupling limits the performance of the current GCSA and degrades the imaging quality. The degradation is mainly caused by two reasons: the residual high-order coupling phase and the non-negligible error introduced by the linear approximation of stationary phase point using the principle of stationary phase (POSP). According to the characteristics of a high-resolution low frequency SAR signal, this paper firstly presents a principle to determine the required order of range frequency. After compensating for the range-independent coupling phase above 3rd order, an improved GCSA based on Lagrange inversion theorem is analytically derived. The Lagrange inversion enables the high-order range-dependent coupling phase to be accurately compensated. Imaging results of P- and L-band SAR data demonstrate the excellent performance of the proposed algorithm compared to the existing GCSA. The image quality and focusing depth in range dimension are greatly improved. The improved method provides the possibility to efficiently process high-resolution low frequency SAR data with wide swath.
Evaluation of Remotely-Sensed and Model-Based Soil Moisture Products According to Different Soil Type, Vegetation Cover and Climate Regime Using Station-Based Observations over Turkey
Authors: Bulut Burak , Yilmaz M. Tugrul , Afshar Mehdi H. , Şorman A. Ünal , Yücel İsmail , Cosh Michael H. , Şimşek Osman
Published: August 2019

This study evaluates the performance of widely-used remotely sensed- and model-based soil moisture products, including: The Advanced Scatterometer (ASCAT), the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E), the European Space Agency Climate Change Initiative (ESA-CCI), the Antecedent Precipitation Index (API), and the Global Land Data Assimilation System (GLDAS-NOAH). Evaluations are performed between 2008 and 2011 against the calibrated station-based soil moisture observations collected by the General Directorate of Meteorology of Turkey. The calibration of soil moisture observing sensors with respect to the soil type, correction of the soil moisture for the soil temperature, and the quality control of the collected measurements are performed prior to the evaluation of the products. Evaluation of remotely sensed- and model-based soil moisture products is performed considering different characteristics of the time series (i.e., seasonality and anomaly components) and the study region (i.e., soil type, vegetation cover, soil wetness and climate regime). The systematic bias between soil moisture products and in situ measurements is eliminated by using a linear rescaling method. Correlations between the soil moisture products and the in situ observations vary between 0.57 and 0.87, while the root mean square errors of the products versus the in situ observations vary between 0.028 and 0.043 m3 m−3. Overall, according to the correlation and root mean square error values obtained in all evaluation categories, NOAH and ESA-CCI soil moisture products perform better than all the other model- and remotely sensed-based soil moisture products. These results are valid for the entire study time period and all of the sub-categories under soil type, vegetation cover, soil wetness and climate regime.
Accurate Geo-Referencing of Trees with No or Inaccurate Terrestrial Location Devices
Authors: Strimbu Bogdan M. , Qi Chu , Sessions John
Published: August 2019

Accurate and precise location of trees from data acquired under-the-canopy is challenging and time-consuming. However, current forestry practices would benefit tremendously from the knowledge of tree coordinates, particularly when the information used to position them is acquired with inexpensive sensors. Therefore, the objective of our study is to geo-reference trees using point clouds created from the images acquired below canopy. We developed a procedure that uses the coordinates of the trees seen from above canopy to position the same trees seen below canopy. To geo-reference the trees from above canopy we captured images with an unmanned aerial vehicle. We reconstructed the trunk with photogrammetric point clouds built with a structure–from–motion procedure from images recorded in a circular pattern at multiple locations throughout the stand. We matched the trees segmented from below canopy with the trees extracted from above canopy using a non-rigid point-matching algorithm. To ensure accuracy, we reduced the number of matching trees by dividing the trees segmented from above using a grid with 50 m cells. Our procedure was implemented on a 7.1 ha Douglas-fir stand from Oregon USA. The proposed procedure is relatively fast, as approximately 600 trees were mapped in approximately 1 min. The procedure is sensitive to the point density, directly impacting tree location, as differences larger than 2 m between the coordinates of the tree top and the bottom part of the stem could lead to matching errors larger than 1 m. Furthermore, the larger the number of trees to be matched the higher the accuracy is, which could allow for misalignment errors larger than 2 m between the locations of the trees segmented from above and below.
Multi-Source Data Integration to Investigate a Deep-Seated Landslide Affecting a Bridge
Authors: Pastor José Luis , Tomás Roberto , Lettieri Luca , Riquelme Adrián , Cano Miguel , Infante Donato , Ramondini Massimo , Di Martire Diego
Published: August 2019

The integration of data from different sources can be very helpful in understanding the mechanism, the geometry, the kinematic, and the area affected by complex instabilities, especially when the available geotechnical information is limited. In this work, the suitability of different techniques for the study of a deep-seated landslide affecting a bridge in Alcoy (Spain) is evaluated. This infrastructure presents such severe damage that has rendered the bridge unusable, which prevents normal access to an important industrial area. Differential SAR Interferometry (DInSAR) and terrestrial Light Detection and Ranging (LiDAR) remote sensing techniques have been combined with ground displacement monitoring techniques, such as inclinometers and conventional geological and geotechnical investigation, electrical-seismic tomography, damage, and topographic surveys, to determine the boundaries, mechanism, and kinematics of the landslide. The successful case study that is illustrated in this work highlights the potential and the need for integrating multi-source data for the optimal management of complex landslides and the effective design of remedial measurements.
The Consistency of SSM/I vs. SSMIS and the Influence on Snow Cover Detection and Snow Depth Estimation over China
Authors: Yang Jianwei , Jiang Lingmei , Dai Liyun , Pan Jinmei , Wu Shengli , Wang Gongxue
Published: August 2019

The long-term variations in snow depth are important in hydrological, meteorological, and ecological implications and climatological studies. The series of Special Sensor Microwave/Imager (SSM/I) and Special Sensor Microwave Imager Sounder (SSMIS) instruments onboard the Defense Meteorological Satellite Program (DMSP) platforms has provided a consistent 30+ year data record of global observations that is well-suited for the estimation of snow cover, snow depth, and snow water equivalent (SWE). To maximize the use of this continuous microwave observation dataset in long-term snow analysis and obtain an objective result, consistency among the SSM/I and SSMIS sensors is required. In this paper, we evaluated the consistency between the SSM/I and SSMIS concerning the observed brightness temperature (Tb) and the retrieved snow cover area and snow depth from January 2007 to December 2008, where the F13 SSM/I and the F17 SSMIS overlapped. Results showed that Tb bias at 19 GHz spans from −2 to −3 K in snow winter seasons, and from −4 to −5 K in non-snow seasons. There is a slight Tb bias at 37 GHz from −2 to 2 K, regardless of season. For 85 (91) GHz, the bias presents some uncertainty from the scattering effect of the snowpack and atmospheric emission. The overall consistency between SSM/I and SSMIS with respect to snow cover detection is between 80% and 100%, which will result in a maximum snow cover area difference of 25 × 104 km2 in China. The inconsistency in Tb between SSM/I and SSMIS can result in a −2 and −0.67 cm snow depth bias for the dual-channel and multichannel algorithms, respectively. SSMIS tends to yield lower snow depth estimates than SSM/I. Moreover, there are notable bias differences between SSM/I- and SSMIS-estimated snow depths in the tundra and taiga snow classes. Our results indicate the importance of considering the Tb bias in microwave snow cover detection and snow depth retrieval and point out that, due to the sensitivity of bias to seasons, it is better to do the intercalibration with a focus on snow-covered winter seasons. Otherwise, the bias in summer will disturb the calibration coefficients and introduce more error into the snow retrievals if the seasonal difference is not carefully evaluated and separated.
A New Adaptive Image Interpolation Method to Define the Shoreline at Sub-Pixel Level
Authors: Sánchez-García Elena , Balaguer-Beser Ángel , Almonacid-Caballer Jaime , Pardo-Pascual Josep Eliseu
Published: August 2019

This paper presents a new methodological process for detecting the instantaneous land-water border at sub-pixel level from mid-resolution satellite images (30 m/pixel) that are freely available worldwide. The new method is based on using an iterative procedure to compute Laplacian roots of a polynomial surface that represents the radiometric response of a set of pixels. The method uses a first approximation of the shoreline at pixel level (initial pixels) and selects a set of neighbouring pixels to be part of the analysis window. This adaptive window collects those stencils in which the maximum radiometric variations are found by using the information given by divided differences. Therefore, the land-water surface is computed by a piecewise interpolating polynomial that models the strong radiometric changes between both interfaces. The assessment is tested on two coastal areas to analyse how their inherent differences may affect the method. A total of 17 Landsat 7 and 8 images (L7 and L8) were used to extract the shorelines and compare them against other highly accurate lines that act as references. Accurate quantitative coastal data from the satellite images is obtained with a mean horizontal error of 4.38 ± 5.66 m and 1.79 ± 2.78 m, respectively, for L7 and L8. Prior methodologies to reach the sub-pixel shoreline are analysed and the results verify the solvency of the one proposed.
Studying the Construction of Floor Mosaics in the Roman Villa of Pisões (Portugal) Using Noninvasive Methods: High-Resolution 3D GPR and Photogrammetry
Authors: Caldeira Bento , Oliveira Rui Jorge , Teixidó Teresa , Borges José Fernando , Henriques Renato , Carneiro André , Peña José Antonio
Published: August 2019

Over the past decade, high-resolution noninvasive sensors have been widely used in explorations of the first few meters underground at archaeological sites. However, remote sensing actions aimed at the study of structural elements that require a very high resolution are rare. In this study, layer characterization of the floor mosaic substrate of the Pisões Roman archaeological site was carried out. This work was performed with two noninvasive techniques: 3D ground penetrating radar (3D GPR) operating with a 1.6 GHz central frequency antenna, which is a very high-resolution geophysical method, and photogrammetry with imagery obtained by an unmanned aerial vehicle (UAV), which is a very high-resolution optical method. The first method allows penetration up to 30–40 cm depth and 3D models can be obtained, and with the second method, very high detail surface images and digital surface models can be obtained. In this study, we analyze a combination of data from both sensors to study a portion of the floor mosaic of the Pisões Roman Villa (Beja, Portugal) to obtain evidence of the inner structure. In this context, we have detected the main structural levels of the Roman mosaic and some internal characteristics, such as etched guides, internal cracking, and detection of higher humidity areas. The methodology that we introduce in this work can be referenced for the documentation of ancient pavements and may be used prior to carrying out preservation activities. Additionally, we intend to show that a Roman mosaic, understood as an archaeological structure, does not consist of only beautiful superficial drawings defined by the tesserae, but these mosaics are much more complex elements that must be considered in their entirety for preservation.
Improved Time-Synchronization Algorithm Based on Direct Compensation of Disturbance Effects
Authors: Seo Yeoung-Duk , Son Kyou Jung , An Gi-Sung , Nam Kyung Deok , Chang Tae Gyu , Kang Sang-Hee
Published: August 2019

In this paper, an improved time-synchronization algorithm is proposed. The improvement of time synchronizing performance was achieved by introducing a stochastic model-based direct compensation of the disturbance effects appearing in the IEEE 1588 Precision Time Protocol (PTP)-based time synchronization system. A dynamic model of PTP clock system was obtained by reflecting the three major sources of disturbances, i.e., clock frequency drift, clock rate offset, and network noise. With the application of the dynamic model of the PTP clock system, the effects of the disturbances can be effectively eliminated in the PTP time synchronization control loop. Computer simulations are performed to verify the performance of the proposed time synchronization algorithm by applying the various types of disturbances, including network noise and clock drift. The simulation results are compared with those of other representative time synchronization algorithms, i.e., IEEE 1588 PTP algorithm and Kalman-filter-based algorithm. It is shown that the proposed algorithm improves time synchronizing performance up to 84% with respect to that of the Kalman-filter-based synchronization algorithm when simulated with colored noise type disturbances. The proposed time synchronization algorithm is expected to contribute for the realization of future Ethernet-based industry-plant monitoring and control including IEC 61850-based digital substation.
Localized Trajectories for 2D and 3D Action Recognition
Authors: Papadopoulos Konstantinos , Demisse Girum , Ghorbel Enjie , Antunes Michel , Aouada Djamila , Ottersten Björn
Published: August 2019

The Dense Trajectories concept is one of the most successful approaches in action recognition, suitable for scenarios involving a significant amount of motion. However, due to noise and background motion, many generated trajectories are irrelevant to the actual human activity and can potentially lead to performance degradation. In this paper, we propose Localized Trajectories as an improved version of Dense Trajectories where motion trajectories are clustered around human body joints provided by RGB-D cameras and then encoded by local Bag-of-Words. As a result, the Localized Trajectories concept provides an advanced discriminative representation of actions. Moreover, we generalize Localized Trajectories to 3D by using the depth modality. One of the main advantages of 3D Localized Trajectories is that they describe radial displacements that are perpendicular to the image plane. Extensive experiments and analysis were carried out on five different datasets.
Maize Silage Kernel Fragment Estimation Using Deep Learning-Based Object Recognition in Non-Separated Kernel/Stover RGB Images
Authors: Rasmussen Christoffer Bøgelund , Moeslund Thomas B.
Published: August 2019

Efficient and robust evaluation of kernel processing from corn silage is an important indicator to a farmer to determine the quality of their harvested crop. Current methods are cumbersome to conduct and take between hours to days. We present the adoption of two deep learning-based methods for kernel processing prediction without the cumbersome step of separating kernels and stover before capturing images. The methods show that kernels can be detected both with bounding boxes and at pixel-level instance segmentation. Networks were trained on up to 1393 images containing just over 6907 manually annotated kernel instances. Both methods showed promising results despite the challenging setting, with an average precision at an intersection-over-union of 0.5 of 34.0% and 36.1% on the test set consisting of images from three different harvest seasons for the bounding-box and instance segmentation networks respectively. Additionally, analysis of the correlation between the Kernel Processing Score (KPS) of annotations against the KPS of model predictions showed a strong correlation, with the best performing at r(15) = 0.88, p = 0.00003. The adoption of deep learning-based object recognition approaches for kernel processing measurement has the potential to lower the quality assessment process to minutes, greatly aiding a farmer in the strenuous harvesting season.
A Force-Sensor-Based Method to Eliminate Deformation of Large Crankshafts during Measurements of Their Geometric Condition
Authors: Nozdrzykowski Krzysztof , Chybowski Leszek
Published: August 2019

This article describes an innovative method for eliminating deformation in large crankshafts during measurement of their geometric condition. The currently available techniques for measuring crankshaft geometry are introduced and classified according to their applicability and the method of measurement. The drawbacks of the methods have been identified and a solution to these problems has been proposed. The influence of the rigid support of a shaft on its deformation, and thus on the reduction in the accuracy of crankshaft geometry measurements, has also been investigated. The concept and main versions of the proposed measuring system with active compensation for shaft deflection, by means of actuators cooperating with force transducers monitoring the deflection of individual crank journals of a crankshaft being measured, have been presented and the flexible support control system has also been described. The problems relating to the operation of the control system have been furnished along with a way to solve them, including the issue of noise reduction in the signal from the force transducer and the influence of the controller parameters on the operation of the flexible support. The computer system that controls the flexible supports has been briefly characterized, and the performance of the prototype system and the model reference system has been compared. The results have shown that the system is able to effectively eliminate the deflection and elastic deformation of the crankshaft under the influence of its own weight.
A limiting Current Oxygen Sensor Constituted of (CeO2)0.95(Y2O3)0.05 as Solid Electrolyte Layer and (CeO2)0.75(ZrO2)0.25 as Dense Diffusion Barrier Layer
Authors: Wang Xiangnan , Liu Tao , Yu Jingkun
Published: August 2019

Using the co-precipitation method to synthesize (CeO2)0.95(Y2O3)0.05 (YDC) and solid reaction method to synthesize (CeO2)0.75(ZrO2)0.25 (ZDC), and the crystal structure, micro-structure, total conductivity and electronic conductivity of the two materials was measured with X-ray diffraction (XRD), scanning electron microscope (SEM), DC van der Pauw and Hebb-Wagner methods. A limiting current oxygen sensor was prepared with YDC solid electrolyte and a ZDC dense diffusion barrier layer by employing platinum pasting bonding. Sensing characteristics of the sensor were obtained at different conditions, including temperature (T), oxygen concentration (x(O2)) and water vapor pressure (p(H2O)), and the influence of various conditions on sensing performance was studied. The long-term stability of the sensor was measured in an oxygen concentration of 1.2% and at a temperature of 800 °C for 120 h. XRD results show that the phase structure of both YDC and ZDC belongs to the cubic phase. SEM results show that both YDC and ZDC layers are dense layers, which are then qualified to be the composition materials of the sensor. The limiting current (IL) of the sensor is obtained and the sensor exhibits good sensing characteristics to satisfy the Knudsen model. Log(IL·T) depends linearly on 1000/T with a squared correlation coefficient (R2) of 0.9904; IL depends linearly on x(O2) with an R2 of 0.9726; and sensing characteristics are not affected by p(H2O). It was found that the oxygen sensor has good long-term stability.
Activity Recognition for IoT Devices Using Fuzzy Spatio-Temporal Features as Environmental Sensor Fusion
Authors: López Medina Miguel Ángel , Espinilla Macarena , Paggeti Cristiano , Medina Quero Javier
Published: August 2019

The IoT describes a development field where new approaches and trends are in constant change. In this scenario, new devices and sensors are offering higher precision in everyday life in an increasingly less invasive way. In this work, we propose the use of spatial-temporal features by means of fuzzy logic as a general descriptor for heterogeneous sensors. This fuzzy sensor representation is highly efficient and enables devices with low computing power to develop learning and evaluation tasks in activity recognition using light and efficient classifiers. To show the methodology’s potential in real applications, we deploy an intelligent environment where new UWB location devices, inertial objects, wearable devices, and binary sensors are connected with each other and describe daily human activities. We then apply the proposed fuzzy logic-based methodology to obtain spatial-temporal features to fuse the data from the heterogeneous sensor devices. A case study developed in the UJAmISmart Lab of the University of Jaen (Jaen, Spain) shows the encouraging performance of the methodology when recognizing the activity of an inhabitant using efficient classifiers.
3D-Printing Techniques on the Development of Multiparameter Sensors Using One FBG
Authors: Leal-Junior Arnaldo , Díaz Camilo , Marques Carlos , Frizera Anselmo , Pontes Maria
Published: August 2019

We report the development of a fiber Bragg grating (FBG) sensor for multiparameter sensing using only one FBG. The FBG was half-embedded in a 3D-printed structure, which resulted in a division of the grating spectrum creating two peaks with different sensitivities with respect to different physical parameters. A numerical analysis of the proposed technique was performed using the coupled-mode theory with modified transfer matrix formulation. Then, experimental analyses were performed as function of temperature, strain and force, where the peaks showed different sensitivities in all analyzed cases. Such results enable the application of a technique for simultaneous measurement of multiple physical parameters using both peaks and the full width half maximum of the FBG embedded in a 3D structure. In the simultaneous multiparameter assessment, the proposed sensor system was able to estimate the three tested parameters (strain, temperature and force) with relative errors as low as 4%.
Drive Force and Longitudinal Dynamics Estimation in Heavy-Duty Vehicles
Authors: Girbés Vicent , Hernández Daniel , Armesto Leopoldo , Dols Juan F. , Sala Antonio
Published: August 2019

Modelling the dynamic behaviour of heavy vehicles, such as buses or trucks, can be very useful for driving simulation and training, autonomous driving, crash analysis, etc. However, dynamic modelling of a vehicle is a difficult task because there are many subsystems and signals that affect its behaviour. In addition, it might be hard to combine data because available signals come at different rates, or even some samples might be missed due to disturbances or communication issues. In this paper, we propose a non-invasive data acquisition hardware/software setup to carry out several experiments with an urban bus, in order to collect data from one of the internal communication networks and other embedded systems. Subsequently, non-conventional sampling data fusion using a Kalman filter has been implemented to fuse data gathered from different sources, connected through a wireless network (the vehicle’s internal CAN bus messages, IMU, GPS, and other sensors placed in pedals). Our results show that the proposed combination of experimental data gathering and multi-rate filtering algorithm allows useful signal estimation for vehicle identification and modelling, even when data samples are missing.
Performance Evaluation and Interference Characterization of Wireless Sensor Networks for Complex High-Node Density Scenarios
Authors: Celaya-Echarri Mikel , Azpilicueta Leyre , López-Iturri Peio , Aguirre Erik , Falcone Francisco
Published: August 2019

The uncontainable future development of smart regions, as a set of smart cities’ networks assembled, is directly associated with a growing demand of full interactive and connected ubiquitous smart environments. To achieve this global connection goal, large numbers of transceivers and multiple wireless systems will be involved to provide user services and applications anytime and anyplace, regardless the devices, networks, or systems they use. Adequate, efficient and effective radio wave propagation tools, methodologies, and analyses in complex indoor and outdoor environments are crucially required to prevent communication limitations such as coverage, capacity, speed, or channel interferences due to high-node density or channel restrictions. In this work, radio wave propagation characterization in an urban indoor and outdoor wireless sensor network environment has been assessed, at ISM 2.4 GHz and 5 GHz frequency bands. The selected scenario is an auditorium placed in an open free city area surrounded by inhomogeneous vegetation. User density within the scenario, in terms of inherent transceivers density, poses challenges in overall system operation, given by multiple node operation which increases overall interference levels. By means of an in-house developed 3D ray launching (3D-RL) algorithm with hybrid code operation, the impact of variable density wireless sensor network operation is presented, providing coverage/capacity estimations, interference estimation, device level performance and precise characterization of multipath propagation components in terms of received power levels and time domain characteristics. This analysis and the proposed simulation methodology, can lead in an adequate interference characterization extensible to a wide range of scenarios, considering conventional transceivers as well as wearables, which provide suitable information for the overall network performance in crowded indoor and outdoor complex heterogeneous environments.
Load-Independent Characterization of Plate Foundation Support Using High-Resolution Distributed Fiber-Optic Sensing
Authors: Skar Asmus , Klar Assaf , Levenberg Eyal
Published: August 2019

The evaluation of soil reaction in geotechnical foundation systems such as concrete pavements, mat- and raft foundations is a challenging task, as the process involves both the selection of a representative mechanical model (e.g., Winkler, Continuum, Pasternak, etc.) and identify its prevailing parameters. Moreover, the support characteristics may change with time and environmental situation. This paper presents a new method for the characterization of plate foundation support using high-resolution fiber-optic distributed strain sensing. The approach involves tracking the location of distinct points of zero and maximum strains, and relating the shift in their location to the changes in soil reaction. The approach may allow the determination of the most suited mechanical model of soil representation as well as model parameters. Routine monitoring using this approach may help to asses the degradation of the subsoil with time as part of structural health monitoring strategies. In this paper, fundamental expressions that relate between the location of distinct strain points and the variation of soil parameters were developed based on various analytical foundation support models. Finally, as an initial validation step and to underpin the idea basics, the proposed method was successfully demonstrated on a simple mechanical setup. It is shown that the approach allows for load-independent characterization of the soil response and, in that sense, it is superior to common identification methods.
A Wide-Band Digital Lock-In Amplifier and Its Application in Microfluidic Impedance Measurement
Authors: Huang Kan , Geng Yangye , Zhang Xibin , Chen Dihu , Cai Zhigang , Wang Min , Zhu Zhen , Wang Zixin
Published: August 2019

In this work, we report on the design of a wide-band digital lock-in amplifier (DLIA) of up to 65 MHz and its application for electrical impedance measurements in microfluidic devices. The DLIA is comprised of several dedicated technologies. First, it features a fully differential analog circuit, which includes a preamplifier with a low input noise of 4.4 nV/√Hz, a programmable-gain amplifier with a gain of 52 dB, and an anti-aliasing, fully differential low-pass filter with −76 dB stop-band attenuation. Second, the DLIA has an all-digital phase lock loop, which features a phase deviation of less than 0.02° throughout the frequency range. The phase lock loop utilizes an equally accurate period-frequency measurement, with a sub-ppm precision of frequency detection. Third, a modified clock link is implemented in the DLIA to improve the signal-to-noise ratio of the analog-to-digital converter affected by clock jitter of up to 20 dBc. A series of measurements were performed to characterize the DLIA, and the results showed an accurate performance. Additionally, impedance measurements of standard-size microparticles were performed by frequency sweep from 300 kHz to 30 MHz, using the DLIA in a microfluidic device. Different diameters of microparticle could be accurately distinguished according to the relative impedance at 2.5 MHz. The results confirm the promising applications of the DLIA in microfluidic electrical impedance measurements.
Hydrogel Microdomain Encapsulation of Stable Functionalized Silver Nanoparticles for SERS pH and Urea Sensing
Authors: Quinn Alexander , You Yil-Hwan , McShane Michael J.
Published: August 2019

Conceptual and commercial examples of implantable sensors have been limited to a relatively small number of target analytes, with a strong focus on glucose monitoring. Recently, surface-enhanced Raman spectroscopy (SERS) pH sensors were demonstrated to track acid-producing enzymatic reactions targeting specific analytes. We show here that SERS pH tracking in the basic regime is also possible, and can be used to monitor urea concentration. To accomplish this, we developed a hydrogel consisting of polyelectrolyte multilayer microcapsules containing a SERS-sensitive pH reporter (4-mercapopyridine capped silver nanoparticles modified with bovine serum albumin). This pH sensing material exhibited a sensitive Raman scattering response to a wide range of pH from 6.5–9.7. By incorporating urease into the hydrogel matrix, the new sensor was capable of distinguishing urea concentrations of 0, 0.1, 1, and 10 mM. We also found that bovine serum albumin (BSA) prevented severe aggregation of the nanoparticle-based pH sensor, which improved sensing range and sensitivity. Furthermore, BSA safeguarded the pH sensor during the encapsulation procedure. Together, the combination of materials represents a novel approach to enabling optical sensing of reactions that generate pH changes in the basic range.
Thermal Drift Investigation of an SOI-Based MEMS Capacitive Sensor with an Asymmetric Structure
Authors: Li Haiwang , Zhai Yanxin , Tao Zhi , Gui Yingxuan , Tan Xiao
Published: August 2019

High-precision, low-temperature-sensitive microelectromechanical system (MEMS) capacitive accelerometers are widely used in aerospace, automotive, and navigation systems. An analytical study of the temperature drift of bias (TDB) and temperature drift of scale factor (TDSF) for an asymmetric comb capacitive accelerometer is presented in this paper. A five-layer model is established for the equivalent expansion ratio in the TDB and TDSF formulas, and the results calculated by the weighted average of thickness and elasticity modulus method are closest to the results of the numerical simulation. The analytical formulas of TDB and TDSF for an asymmetric structure are obtained. For an asymmetric structure, TDB is only related to thermal deformation and fabrication error. Additionally, half of the fixed electrode distance is not included in the expressions of Δ d and Δ D for asymmetric structures, thus resulting in the TDSF of the asymmetric structure being smaller compared to a symmetric structure with the same structural parameters. The TDSF of the symmetric structure is [−200.2 ppm/°C, −261.6 ppm/°C], while the results of the asymmetric structure are [−11.004 ppm/°C, −72.404 ppm/°C] under the same set of parameters. The parameters of the optimal asymmetric structure are obtained for fabrication guidance using numerical methods. In the experiment, the TDSF and TDB of the packaged structure and the non-packaged structure are compared, and a significant effect of the package on the signal output is found. The TDB is reduced from 3000 to 60 μg/°C, while the TDSF is reduced from 3000 to 140 ppm/°C.
Fatigue Performance of Type I Fibre Bragg Grating Strain Sensors
Authors: Zhang Naizhong , Davis Claire , Chiu Wing K. , Boilard Tommy , Bernier Martin
Published: August 2019

Although fibre Bragg gratings (FBGs) offer obvious potential for use in high-density, high-strain sensing applications, the adoption of this technology in the historically conservative aerospace industry has been slow. There are several contributing factors, one of which is variability in the reported performance of these sensors in harsh and fatigue prone environments. This paper reports on a comparative evaluation of the fatigue performance of FBG sensors written according to the same specifications using three different grating manufacturing processes: sensors written in stripped and re-coated fibres, sensors written during the fibre draw process and sensors written through fibre coating. Fatigue cycling of the fibres is provided by a customized electro-dynamically actuated loading assembly designed to provide high frequency and amplitude loading. Pre- and post-fatigue microscopic analysis and high-resolution transmission and reflection spectra scanning are conducted to investigate the fatigue performance of FBGs, the failure regions of fibres as well as any fatigue-related effects on the spectral profiles. It was found that because of the unique fabrication method, the sensors written through the fibre coating, also known as trans-jacket FBGs, show better fatigue performance than stripped and re-coated FBGs with greater control possible to tailor the optical reflection properties compared to gratings written in the draw tower. This emerging method for inscription of Type I gratings opens up the potential for mass production of higher reflectivity, apodised sensors with dense or complex array architectures which can be adopted as sensors for harsh environments such as in defence and aerospace industries.
Agent-Based Modeling of a Self-Organized Food Safety System
Authors: Zia Kashif , Farooq Umar , Muhammad Arshad
Published: August 2019

“The wisdom of crowds” is often observed in social discourses and activities around us. The manifestations of it are, however, so intrinsically embedded and behaviorally accepted that an elaboration of a social phenomenon evidencing such wisdom is often considered a discovery; or at least an astonishing fact. One such scenario is explored here, namely, the conceptualization and modeling of a food safety system—a system directly related to social cognition. The first contribution of this paper is the re-evaluation of Knowles’s model towards a more conscious understanding of “the wisdom of crowds” effects on inspection and consumption behaviors. The second contribution is augmenting the model with social networking capabilities, which acts as a medium to spread information about stores and help consumers find uncontaminated stores. Simulation results revealed that stores respecting social cognition improve the effectiveness of the food safety system for consumers as well as for the stores. Simulation findings also revealed that active societies have the capability to self-organize effectively, even if they lack regulatory obligations.
Which Export Variety Matters for Urban Economic Growth, Related or Unrelated Variety?
Authors: Qin Xiaozhen , Li Shan , Xu Weipan , Li Xun
Published: August 2019

The relationship between export variety and economic growth has been paid much attention in academia. This paper discusses more deeply the relationship between export related and unrelated variety and economic growth, rather than mere export variety. This paper uses the entropy measurement method to measure the level of export variety of Chinese cities and use the concept of “proximity” proposed by Hidalgo to divide the related variety and unrelated variety. Using the panel data of 252 prefecture-level cities in China from 2000 to 2011, we attempt to explore the relationship between export variety, related and unrelated variety and urban economic growth. The empirical results show that it is not export variety as such, but related and unrelated variety that has effects on economic growth. Export related variety has a positive effect on economic growth, while unrelated variety has a negative effect. And there are obvious regional and size differences. The impact of export related and unrelated variety on eastern and coastal cities is greater than that on central and inland cities, and the impact on large-size cities is also greater than that on medium-size cities.