bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparison of Different Machine Learning Approaches for Monthly Satellite-Based Soil Moisture Downscaling over Northeast China
Authors: Liu Yangxiaoyue , Yang Yaping , Jing Wenlong , Yue Xiafang
Published: December 2017

Although numerous satellite-based soil moisture (SM) products can provide spatiotemporally continuous worldwide datasets, they can hardly be employed in characterizing fine-grained regional land surface processes, owing to their coarse spatial resolution. In this study, we proposed a machine-learning-based method to enhance SM spatial accuracy and improve the availability of SM data. Four machine learning algorithms, including classification and regression trees (CART), K-nearest neighbors (KNN), Bayesian (BAYE), and random forests (RF), were implemented to downscale the monthly European Space Agency Climate Change Initiative (ESA CCI) SM product from 25-km to 1-km spatial resolution. During the regression, the land surface temperature (including daytime temperature, nighttime temperature, and diurnal fluctuation temperature), normalized difference vegetation index, surface reflections (red band, blue band, NIR band and MIR band), and digital elevation model were taken as explanatory variables to produce fine spatial resolution SM. We chose Northeast China as the study area and acquired corresponding SM data from 2003 to 2012 in unfrozen seasons. The reconstructed SM datasets were validated against in-situ measurements. The results showed that the RF-downscaled results had superior matching performance to both ESA CCI SM and in-situ measurements, and can positively respond to precipitation variation. Additionally, the RF was less affected by parameters, which revealed its robustness. Both CART and KNN ranked second. Compared to KNN, CART had a relatively close correlation with the validation data, but KNN showed preferable precision. Moreover, BAYE ranked last with significantly abnormal regression values.
Comprehensive Evaluation of Two Successive V3 and V4 IMERG Final Run Precipitation Products over Mainland China
Authors: Zhao Haigen , Yang Shengtian , You Songcai , Huang Yingchun , Wang Qianfeng , Zhou Qiuwen
Published: December 2017

The Integrated Multi-satellitE Retrievals for Global Precipitation Measurement Final Run (IMERGF) product has now been upgraded to Version 4 (V4), which has been available since March 2017. Therefore, it is desirable to evaluate the characteristic differences between the V4 and the previous V3 products. A comprehensive performance evaluation of the errors of the successive V3 and V4 IMERGF products is performed with a comparison of the China daily Precipitation Analysis Products (CPAP) from March 2014 to February 2015. The version 6 Global Satellite Mapping of Precipitation (GSMaP) research product (which is another Global Precipitation Measurement (GPM) based precipitation product) is also used as a comparison in this study. Overall, the IMERGF-V4 product does not exhibit the anticipated improvement for China compared to the IMERGF-V3 product. An analysis of the metrics of annual daily average precipitation over China for the IMERGF-V3 and IMERGF-V4 products indicates a decrease of the relative bias (RB) from 3.70% to −7.18%, a decrease of the correlation coefficient (CC) from 0.91 to 0.89, an increase of the fractional standard error (FSE) from 0.49 to 0.56, and an increase of the root-mean-square error (RMSE) from 0.63 mm to 0.72 mm. Compared to the IMERGF-V3 product, the IMERGF-V4 product exhibits a significant underestimation of precipitation in the Qinghai-Tibetan plateau with a much lower RB of −60.91% (−58.19%, −65.30%, and −63.74%) based on the annual (summer, autumn, and winter) daily average precipitation and an even worse performance during winter (−72.33% of RB). In comparison, the GSMaP product outperforms the IMERGF-V3 and IMERGF-V4 products and has the smallest RMSE (0.47 mm/day), highest CC (0.95), lowest FSE (0.37), and best performance of the RB (−2.39%) in terms of annual daily precipitation over China. However, the GSMaP product underestimates the precipitation more than the IMERGF-V3 product for the arid XJ region.
Gaussian Half-Wavelength Progressive Decomposition Method for Waveform Processing of Airborne Laser Bathymetry
Authors: Guo Kai , Xu Wenxue , Liu Yanxiong , He Xiufeng , Tian Ziwen
Published: December 2017

In an airborne laser bathymetry system, the full-waveform echo signal is usually recorded by discrete sampling. The accuracy of signal recognition and the amount of effective information that can be extracted by conventional methods are limited. To improve the validity and reliability of airborne laser bathymetry data and to extract more information to better understand the water reflection characteristics, we select the effective portion of the original waveform for further research, suppress random noise, and decompose the selected portion progressively using the half-wavelength Gaussian function with the time sequence of the received echo signals. After parameter optimization, a reasonable and effective reflection component selection mechanism is established to obtain accurate parameters for the reflected components. The processing strategy proposed in this paper reduces the problems of unreasonable decomposition and the reflected pulse peak-position shift caused by echo waveform superposition and offers good precision for waveform decomposition and peak detection. In another experiment, the regional processing result shows an obvious improvement in the shallow water area, and the bottom point cloud is as accurate as the intelligent waveform digitizer (IWD), a subsystem of airborne laser terrain mapping (ALTM). These findings confirm that the proposed method has high potential for application.
Inter-Calibration of Passive Microwave Satellite Brightness Temperatures Observed by F13 SSM/I and F17 SSMIS for the Retrieval of Snow Depth on Arctic First-Year Sea Ice
Authors: Liu Qingquan , Ji Qing , Pang Xiaoping , Gao Xin , Zhao Xi , Lei Ruibo
Published: December 2017

Passive microwave satellite brightness temperatures (TB) that were observed by the F13 Special Sensor Microwave/Imager (SSM/I) and the subsequent F17 Special Sensor Microwave Imager/Sounder (SSMIS) were inter-calibrated using empirical relationship models during their overlap period. Snow depth (SD) on the Arctic first-year sea ice was further retrieved. The SDs derived from F17 TB and F13C TB which were calibrated F17 TB using F13 TB as the baseline were then compared and evaluated against in situ SD measurements based on the Operational IceBridge (OIB) airborne observations from 2009 to 2013. Results show that Cavalieri inter-calibration models (CA models) perform smaller root mean square error (RMSE) than Dai inter-calibration models (DA models), and the standard deviation of OIB SDs in the 25 km pixels is around 6 cm on first-year sea ice. Moreover, the SDs derived from the calibrated F17 TB using F13 TB as the baseline were in better agreement than the F17 SDs as compared with OIB SDs, with the biases of −2 cm (RMSE of 5 cm) and −9 cm (RMSE of 10 cm), respectively. We conclude that TB observations from F17 SSMIS calibrated to F13 SSM/I as the baseline should be recommended when performing the sensors’ biases correction for SD purpose based on the existing algorithm. These findings could serve as a reference for generating more consistent and reliable TB, which could help to improve the retrieval and analysis of long-term snow depth on the Arctic first-year sea ice.
Bayesian and Classical Machine Learning Methods: A Comparison for Tree Species Classification with LiDAR Waveform Signatures
Authors: Zhou Tan , Popescu Sorin , Lawing A. , Eriksson Marian , Strimbu Bogdan , Bürkner Paul
Published: December 2017

A plethora of information contained in full-waveform (FW) Light Detection and Ranging (LiDAR) data offers prospects for characterizing vegetation structures. This study aims to investigate the capacity of FW LiDAR data alone for tree species identification through the integration of waveform metrics with machine learning methods and Bayesian inference. Specifically, we first conducted automatic tree segmentation based on the waveform-based canopy height model (CHM) using three approaches including TreeVaW, watershed algorithms and the combination of TreeVaW and watershed (TW) algorithms. Subsequently, the Random forests (RF) and Conditional inference forests (CF) models were employed to identify important tree-level waveform metrics derived from three distinct sources, such as raw waveforms, composite waveforms, the waveform-based point cloud and the combined variables from these three sources. Further, we discriminated tree (gray pine, blue oak, interior live oak) and shrub species through the RF, CF and Bayesian multinomial logistic regression (BMLR) using important waveform metrics identified in this study. Results of the tree segmentation demonstrated that the TW algorithms outperformed other algorithms for delineating individual tree crowns. The CF model overcomes waveform metrics selection bias caused by the RF model which favors correlated metrics and enhances the accuracy of subsequent classification. We also found that composite waveforms are more informative than raw waveforms and waveform-based point cloud for characterizing tree species in our study area. Both classical machine learning methods (the RF and CF) and the BMLR generated satisfactory average overall accuracy (74% for the RF, 77% for the CF and 81% for the BMLR) and the BMLR slightly outperformed the other two methods. However, these three methods suffered from low individual classification accuracy for the blue oak which is prone to being misclassified as the interior live oak due to the similar characteristics of blue oak and interior live oak. Uncertainty estimates from the BMLR method compensate for this downside by providing classification results in a probabilistic sense and rendering users with more confidence in interpreting and applying classification results to real-world tasks such as forest inventory. Overall, this study recommends the CF method for feature selection and suggests that BMLR could be a superior alternative to classical machining learning methods.
Implementation of a Virtual Microphone Array to Obtain High Resolution Acoustic Images
Authors: Izquierdo Alberto , Villacorta Juan , Del Val Lara , Suárez Luis , Suárez David
Published: December 2017

Using arrays with digital MEMS (Micro-Electro-Mechanical System) microphones and FPGA-based (Field Programmable Gate Array) acquisition/processing systems allows building systems with hundreds of sensors at a reduced cost. The problem arises when systems with thousands of sensors are needed. This work analyzes the implementation and performance of a virtual array with 6400 (80 × 80) MEMS microphones. This virtual array is implemented by changing the position of a physical array of 64 (8 × 8) microphones in a grid with 10 × 10 positions, using a 2D positioning system. This virtual array obtains an array spatial aperture of 1 × 1 m2. Based on the SODAR (SOund Detection And Ranging) principle, the measured beampattern and the focusing capacity of the virtual array have been analyzed, since beamforming algorithms assume to be working with spherical waves, due to the large dimensions of the array in comparison with the distance between the target (a mannequin) and the array. Finally, the acoustic images of the mannequin, obtained for different frequency and range values, have been obtained, showing high angular resolutions and the possibility to identify different parts of the body of the mannequin.
Uniformity Study of Two-Functional Luminescent Dyes Adsorbed over an Anodized Aluminum Coating for Motion-Capturing Pressure- and Temperature-Sensitive Paint Imaging
Authors: Ishii Masato , Miyazaki Takeshi , Sakaue Hirotaka
Published: December 2017

The pressure- and temperature-sensitive paint (PSP/TSP) technique, for steady-state and unsteady-state measurements, is becoming widespread. However, unsteady quantitative measurement is still difficult because non-uniform distribution of the probes over a test model may cause errors in the results. We focus on the dipping method that applies two luminophores into a binding material to improve sensitivity uniformity over a model surface. A bullet-shaped axisymmetric test model with motion-capturing TSP was used to evaluate the sensitivity uniformity, and three dipping methods (static, convectional, and rotational) were examined. The average peak ratios in the longitudinal direction were 1.17–1.46 for static, 1.38–1.51 for convectional, and 1.42–1.45 for rotational dipping. The standard deviations in the transverse direction were the smallest for rotational (0.022–0.033), relative to static (0.086–0.104), and convectional (0.044–0.065) dipping.
GTSO: Global Trace Synchronization and Ordering Mechanism for Wireless Sensor Network Monitoring Platforms
Authors: Navia Marlon , Campelo José , Bonastre Alberto , Ors Rafael
Published: December 2017

Monitoring is one of the best ways to evaluate the behavior of computer systems. When the monitored system is a distributed system—such as a wireless sensor network (WSN)—the monitoring operation must also be distributed, providing a distributed trace for further analysis. The temporal sequence of occurrence of the events registered by the distributed monitoring platform (DMP) must be correctly established to provide cause-effect relationships between them, so the logs obtained in different monitor nodes must be synchronized. Many of synchronization mechanisms applied to DMPs consist in adjusting the internal clocks of the nodes to the same value as a reference time. However, these mechanisms can create an incoherent event sequence. This article presents a new method to achieve global synchronization of the traces obtained in a DMP. It is based on periodic synchronization signals that are received by the monitor nodes and logged along with the recorded events. This mechanism processes all traces and generates a global post-synchronized trace by scaling all times registered proportionally according with the synchronization signals. It is intended to be a simple but efficient offline mechanism. Its application in a WSN-DMP demonstrates that it guarantees a correct ordering of the events, avoiding the aforementioned issues.
A Low-Cost Approach to Automatically Obtain Accurate 3D Models of Woody Crops
Authors: Bengochea-Guevara José , Andújar Dionisio , Sanchez-Sardana Francisco , Cantuña Karla , Ribeiro Angela
Published: December 2017

Crop monitoring is an essential practice within the field of precision agriculture since it is based on observing, measuring and properly responding to inter- and intra-field variability. In particular, “on ground crop inspection” potentially allows early detection of certain crop problems or precision treatment to be carried out simultaneously with pest detection. “On ground monitoring” is also of great interest for woody crops. This paper explores the development of a low-cost crop monitoring system that can automatically create accurate 3D models (clouds of coloured points) of woody crop rows. The system consists of a mobile platform that allows the easy acquisition of information in the field at an average speed of 3 km/h. The platform, among others, integrates an RGB-D sensor that provides RGB information as well as an array with the distances to the objects closest to the sensor. The RGB-D information plus the geographical positions of relevant points, such as the starting and the ending points of the row, allow the generation of a 3D reconstruction of a woody crop row in which all the points of the cloud have a geographical location as well as the RGB colour values. The proposed approach for the automatic 3D reconstruction is not limited by the size of the sampled space and includes a method for the removal of the drift that appears in the reconstruction of large crop rows.
Redundancy Analysis of Capacitance Data of a Coplanar Electrode Array for Fast and Stable Imaging Processing
Authors: Wen Yintang , Zhang Zhenda , Zhang Yuyan , Sun Dongtao
Published: December 2017

A coplanar electrode array sensor is established for the imaging of composite-material adhesive-layer defect detection. The sensor is based on the capacitive edge effect, which leads to capacitance data being considerably weak and susceptible to environmental noise. The inverse problem of coplanar array electrical capacitance tomography (C-ECT) is ill-conditioning, in which a small error of capacitance data can seriously affect the quality of reconstructed images. In order to achieve a stable image reconstruction process, a redundancy analysis method for capacitance data is proposed. The proposed method is based on contribution rate and anti-interference capability. According to the redundancy analysis, the capacitance data are divided into valid and invalid data. When the image is reconstructed by valid data, the sensitivity matrix needs to be changed accordingly. In order to evaluate the effectiveness of the sensitivity map, singular value decomposition (SVD) is used. Finally, the two-dimensional (2D) and three-dimensional (3D) images are reconstructed by the Tikhonov regularization method. Through comparison of the reconstructed images of raw capacitance data, the stability of the image reconstruction process can be improved, and the quality of reconstructed images is not degraded. As a result, much invalid data are not collected, and the data acquisition time can also be reduced.
Assessment of Blue Carbon Storage by Baja California (Mexico) Tidal Wetlands and Evidence for Wetland Stability in the Face of Anthropogenic and Climatic Impacts
Authors: Watson Elizabeth , Hinojosa Corona Alejandro
Published: December 2017

Although saline tidal wetlands cover less than a fraction of one percent of the earth’s surface (~0.01%), they efficiently sequester organic carbon due to high rates of primary production coupled with surfaces that aggrade in response to sea level rise. Here, we report on multi-decadal changes (1972–2008) in the extent of tidal marshes and mangroves, and characterize soil carbon density and source, for five regions of tidal wetlands located on Baja California’s Pacific coast. Land-cover change analysis indicates the stability of tidal wetlands relative to anthropogenic and climate change impacts over the past four decades, with most changes resulting from natural coastal processes that are unique to arid environments. The disturbance of wetland soils in this region (to a depth of 50 cm) would liberate 2.55 Tg of organic carbon (C) or 9.36 Tg CO2eq. Based on stoichiometry and carbon stable isotope ratios, the source of organic carbon in these wetland sediments is derived from a combination of wetland macrophyte, algal, and phytoplankton sources. The reconstruction of natural wetland dynamics in Baja California provides a counterpoint to the history of wetland destruction elsewhere in North America, and measurements provide new insights on the control of carbon sequestration in arid wetlands.
U-Shaped and Surface Functionalized Polymer Optical Fiber Probe for Glucose Detection
Authors: Azkune Mikel , Ruiz-Rubio Leire , Aldabaldetreku Gotzon , Arrospide Eneko , Pérez-Álvarez Leyre , Bikandi Iñaki , Zubia Joseba , Vilas-Vilela Jose
Published: December 2017

In this work we show an optical fiber evanescent wave absorption probe for glucose detection in different physiological media. High selectivity is achieved by functionalizing the surface of an only-core poly(methyl methacrylate) (PMMA) polymer optical fiber with phenilboronic groups, and enhanced sensitivity by using a U-shaped geometry. Employing a supercontinuum light source and a high-resolution spectrometer, absorption measurements are performed in the broadband visible light spectrum. Experimental results suggest the feasibility of such a fiber probe as a low-cost and selective glucose detector.
Range Sidelobe Suppression Using Complementary Sets in Distributed Multistatic Radar Networks
Authors: Zhu Jiahua , Wang Xuezhi , Song Yongping , Huang Xiaotao , Moran Bill
Published: December 2017

We propose an alternative waveform scheme built on mutually-orthogonal complementary sets for a distributed multistatic radar. Our analysis and simulation show a reduced frequency band requirement for signal separation between antennas with centralized signal processing using the same carrier frequency. While the scheme can tolerate fluctuations of carrier frequencies and phases, range sidelobes arise when carrier frequencies between antennas are significantly different.
Theoretical and Experimental Comparison of Different Formats of Immunochromatographic Serodiagnostics
Authors: Sotnikov Dmitriy , Zherdev Anatoly , Dzantiev Boris
Published: December 2017

In this study, a comparative theoretical and experimental analysis of two immuno-chromatographic serodiagnostics schemes, which differ in the immobilization of immunoreagents and the order of the formation of immune complexes, is performed. Based on the theoretical models, the assays are characterized to determine which scheme has a higher quantity of the detected complex and thus ensures the sensitivity of the analysis. The results show that for the effective detection of low-affinity antibodies, the scheme involving the immobilization of the antigen on gold nanoparticles and the antibody-binding protein on the test strip was more sensitive than the predominantly used scheme, which inverts the immunoreagents’ locations. The theoretical predictions were confirmed by the experimental testing of sera collected from tuberculosis patients.
Fabrication of a P3HT-ZnO Nanowires Gas Sensor Detecting Ammonia Gas
Authors: Kuo Chin-Guo , Chen Jung-Hsuan , Chao Yi-Chieh , Chen Po-Lin
Published: December 2017

In this study, an organic-inorganic semiconductor gas sensor was fabricated to detect ammonia gas. An inorganic semiconductor was a zinc oxide (ZnO) nanowire array produced by atomic layer deposition (ALD) while an organic material was a p-type semiconductor, poly(3-hexylthiophene) (P3HT). P3HT was suitable for the gas sensing application due to its high hole mobility, good stability, and good electrical conductivity. In this work, P3HT was coated on the zinc oxide nanowires by the spin coating to form an organic-inorganic heterogeneous interface of the gas sensor for detecting ammonia gas. The thicknesses of the P3HT were around 462 nm, 397 nm, and 277 nm when the speeds of the spin coating were 4000 rpm, 5000 rpm, and 6000 rpm, respectively. The electrical properties and sensing characteristics of the gas sensing device at room temperature were evaluated by Hall effect measurement and the sensitivity of detecting ammonia gas. The results of Hall effect measurement for the P3HT-ZnO nanowires semiconductor with 462 nm P3HT film showed that the carrier concentration and the mobility were 2.7 × 1019 cm−3 and 24.7 cm2∙V−1∙s−1 respectively. The gas sensing device prepared by the P3HT-ZnO nanowires semiconductor had better sensitivity than the device composed of the ZnO film and P3HT film. Additionally, this gas sensing device could reach a maximum sensitivity around 11.58 per ppm.
Motion Artifact Quantification and Sensor Fusion for Unobtrusive Health Monitoring
Authors: Hoog Antink Christoph , Schulz Florian , Leonhardt Steffen , Walter Marian
Published: December 2017

Sensors integrated into objects of everyday life potentially allow unobtrusive health monitoring at home. However, since the coupling of sensors and subject is not as well-defined as compared to a clinical setting, the signal quality is much more variable and can be disturbed significantly by motion artifacts. One way of tackling this challenge is the combined evaluation of multiple channels via sensor fusion. For robust and accurate sensor fusion, analyzing the influence of motion on different modalities is crucial. In this work, a multimodal sensor setup integrated into an armchair is presented that combines capacitively coupled electrocardiography, reflective photoplethysmography, two high-frequency impedance sensors and two types of ballistocardiography sensors. To quantify motion artifacts, a motion protocol performed by healthy volunteers is recorded with a motion capture system, and reference sensors perform cardiorespiratory monitoring. The shape-based signal-to-noise ratio SNR S is introduced and used to quantify the effect on motion on different sensing modalities. Based on this analysis, an optimal combination of sensors and fusion methodology is developed and evaluated. Using the proposed approach, beat-to-beat heart-rate is estimated with a coverage of 99.5% and a mean absolute error of 7.9 ms on 425 min of data from seven volunteers in a proof-of-concept measurement scenario.
Quantitative Determination of Spring Water Quality Parameters via Electronic Tongue
Authors: Carbó Noèlia , López Carrero Javier , Garcia-Castillo F. , Tormos Isabel , Olivas Estela , Folch Elisa , Alcañiz Fillol Miguel , Soto Juan , Martínez-Máñez Ramón , Martínez-Bisbal M.
Published: December 2017

The use of a voltammetric electronic tongue for the quantitative analysis of quality parameters in spring water is proposed here. The electronic voltammetric tongue consisted of a set of four noble electrodes (iridium, rhodium, platinum, and gold) housed inside a stainless steel cylinder. These noble metals have a high durability and are not demanding for maintenance, features required for the development of future automated equipment. A pulse voltammetry study was conducted in 83 spring water samples to determine concentrations of nitrate (range: 6.9–115 mg/L), sulfate (32–472 mg/L), fluoride (0.08–0.26 mg/L), chloride (17–190 mg/L), and sodium (11–94 mg/L) as well as pH (7.3–7.8). These parameters were also determined by routine analytical methods in spring water samples. A partial least squares (PLS) analysis was run to obtain a model to predict these parameter. Orthogonal signal correction (OSC) was applied in the preprocessing step. Calibration (67%) and validation (33%) sets were selected randomly. The electronic tongue showed good predictive power to determine the concentrations of nitrate, sulfate, chloride, and sodium as well as pH and displayed a lower R2 and slope in the validation set for fluoride. Nitrate and fluoride concentrations were estimated with errors lower than 15%, whereas chloride, sulfate, and sodium concentrations as well as pH were estimated with errors below 10%.
A General Framework for 3-D Parameters Estimation of Roads Using GPS, OSM and DEM Data
Authors: Boucher Christophe , Noyer Jean-Charles
Published: December 2017

A growing number of applications needs GIS mapping information and commercial 3-D roadmaps especially. This paper presents a solution of accessing freely to 3-D map information and updating in the context of transport applications. The method relies on the OSM road networks that is 2-D modeled intrinsically. The objective is to estimate the road elevation and inclination parameters by fusing GPS, OSM and DEM data through a nonlinear filter. An experimental framework, using ASTER GDEM2 data, shows some results of the improvement of the roads modeling that includes their slopes also. The map database can be enriched with the estimated inclinations. The accuracy depends on the GPS and DEM elevation errors (typically a few meters with the GNSS sensors used and the DEM under consideration).
Acousto-Optic Q-Switched Fiber Laser-Based Intra-Cavity Photoacoustic Spectroscopy for Trace Gas Detection
Authors: Zhang Qinduan , Chang Jun , Wang Qiang , Wang Zongliang , Wang Fupeng , Qin Zengguang
Published: December 2017

We proposed a new method for gas detection in photoacoustic spectroscopy based on acousto-optic Q-switched fiber laser by merging a transmission PAS cell (resonant frequency f0 = 5.3 kHz) inside the fiber laser cavity. The Q-switching was achieved by an acousto-optic modulator, achieving a peak pulse power of ~679 mW in the case of the acousto-optic modulation signal with an optimized duty ratio of 10%. We used a custom-made fiber Bragg grating with a central wavelength of 1530.37 nm (the absorption peak of C2H2) to select the laser wavelength. The system achieved a linear response (R2 = 0.9941) in a concentration range from 400 to 7000 ppmv, and the minimum detection limit compared to that of a conventional intensity modulation system was enhanced by 94.2 times.
Sliding Spotlight Mode Imaging with GF-3 Spaceborne SAR Sensor
Authors: Zhang Qingjun , Xiao Feng , Ding Zegang , Ke Meng , Zeng Tao
Published: December 2017

Synthetic aperture radar (SAR) sliding spotlight work mode can achieve high resolutions and wide swath (HRWS) simultaneously by steering the radar antenna beam. This paper aims to obtain well focused images using sliding spotlight mode with the Chinese Gaofen-3 SAR sensor. We proposed an integrated imaging scheme with sliding spotlight echoes. In the imaging scheme, the two-step approach is applied to the spaceborne sliding spotlight SAR imaging algorithm, followed by the Doppler parameter estimation algorithm. The azimuth spectral folding phenomenon is overcome by the two-step approach. The results demonstrate a high Doppler parameter estimation accuracy. The proposed imaging process is accurate and highly efficient for sliding spotlight SAR mode.
Use of Terrestrial Laser Scanner for Rigid Airport Pavement Management
Authors: Barbarella Maurizio , D’Amico Fabrizio , De Blasiis Maria , Di Benedetto Alessandro , Fiani Margherita
Published: December 2017

The evaluation of the structural efficiency of airport infrastructures is a complex task. Faulting is one of the most important indicators of rigid pavement performance. The aim of our study is to provide a new method for faulting detection and computation on jointed concrete pavements. Nowadays, the assessment of faulting is performed with the use of laborious and time-consuming measurements that strongly hinder aircraft traffic. We proposed a field procedure for Terrestrial Laser Scanner data acquisition and a computation flow chart in order to identify and quantify the fault size at each joint of apron slabs. The total point cloud has been used to compute the least square plane fitting those points. The best-fit plane for each slab has been computed too. The attitude of each slab plane with respect to both the adjacent ones and the apron reference plane has been determined by the normal vectors to the surfaces. Faulting has been evaluated as the difference in elevation between the slab planes along chosen sections. For a more accurate evaluation of the faulting value, we have then considered a few strips of data covering rectangular areas of different sizes across the joints. The accuracy of the estimated quantities has been computed too.
A Component-Based Approach for Securing Indoor Home Care Applications
Authors: Agirre Aitor , Armentia Aintzane , Estévez Elisabet , Marcos Marga
Published: December 2017

eHealth systems have adopted recent advances on sensing technologies together with advances in information and communication technologies (ICT) in order to provide people-centered services that improve the quality of life of an increasingly elderly population. As these eHealth services are founded on the acquisition and processing of sensitive data (e.g., personal details, diagnosis, treatments and medical history), any security threat would damage the public’s confidence in them. This paper proposes a solution for the design and runtime management of indoor eHealth applications with security requirements. The proposal allows applications definition customized to patient particularities, including the early detection of health deterioration and suitable reaction (events) as well as security needs. At runtime, security support is twofold. A secured component-based platform supervises applications execution and provides events management, whilst the security of the communications among application components is also guaranteed. Additionally, the proposed event management scheme adopts the fog computing paradigm to enable local event related data storage and processing, thus saving communication bandwidth when communicating with the cloud. As a proof of concept, this proposal has been validated through the monitoring of the health status in diabetic patients at a nursing home.
Research on Ship-Radiated Noise Denoising Using Secondary Variational Mode Decomposition and Correlation Coefficient
Authors: Li Yuxing , Li Yaan , Chen Xiao , Yu Jing
Published: December 2017

As the sound signal of ships obtained by sensors contains other many significant characteristics of ships and called ship-radiated noise (SN), research into a denoising algorithm and its application has obtained great significance. Using the advantage of variational mode decomposition (VMD) combined with the correlation coefficient for denoising, a hybrid secondary denoising algorithm is proposed using secondary VMD combined with a correlation coefficient (CC). First, different kinds of simulation signals are decomposed into several bandwidth-limited intrinsic mode functions (IMFs) using VMD, where the decomposition number by VMD is equal to the number by empirical mode decomposition (EMD); then, the CCs between the IMFs and the simulation signal are calculated respectively. The noise IMFs are identified by the CC threshold and the rest of the IMFs are reconstructed in order to realize the first denoising process. Finally, secondary denoising of the simulation signal can be accomplished by repeating the above steps of decomposition, screening and reconstruction. The final denoising result is determined according to the CC threshold. The denoising effect is compared under the different signal-to-noise ratio and the time of decomposition by VMD. Experimental results show the validity of the proposed denoising algorithm using secondary VMD (2VMD) combined with CC compared to EMD denoising, ensemble EMD (EEMD) denoising, VMD denoising and cubic VMD (3VMD) denoising, as well as two denoising algorithms presented recently. The proposed denoising algorithm is applied to feature extraction and classification for SN signals, which can effectively improve the recognition rate of different kinds of ships.
Amplified Detection of the Aptamer–Vanillin Complex with the Use of Bsm DNA Polymerase
Authors: Andrianova Mariia , Komarova Natalia , Grudtsov Vitaliy , Kuznetsov Evgeniy , Kuznetsov Alexander
Published: December 2017

The electrochemical detection of interactions between aptamers and low-molecular-weight targets often lacks sensitivity. Signal amplification improves the detection of the aptamer-analyte complex; Bsm DNA polymerase was used to amplify the signal from the interaction of vanillin and its aptamer named Van_74 on an ion-sensitive field-effect transistor (ISFET)-based biosensor. The aptamer was immobilized on the ISFET sensitive surface. A short DNA probe was hybridized with the aptamer and dissociated from it upon vanillin addition. A free probe interacted with a special DNA molecular beacon initiated the Bsm DNA polymerase reaction that was detected by ISFET. A buffer solution suitable for both aptamer action and Bsm DNA polymerase activity was determined. The ISFET was shown to detect the Bsm DNA polymerase reaction under the selected conditions. Vanillin at different concentrations (1 × 10−6–1 × 10−8 M) was detected using the biosensor with signal amplification. The developed detection system allowed for the determination of vanillin, starting at a 10−8 M concentration. Application of the Bsm DNA polymerase resulted in a 15.5 times lower LoD when compared to the biosensor without signal amplification (10.1007/s00604-017-2586-4).
UV-Enhanced Ethanol Sensing Properties of RF Magnetron-Sputtered ZnO Film
Authors: Huang Jinyu , Du Yu , Wang Quan , Zhang Hao , Geng Youfu , Li Xuejin , Tian Xiaoqing
Published: December 2017

ZnO film was deposited by the magnetron sputtering method. The thickness of ZnO film is approximately 2 μm. The influence of UV light illumination on C2H5OH sensing properties of ZnO film was investigated. Gas sensing results revealed that the UV-illuminated ZnO film displays excellent C2H5OH characteristics in terms of high sensitivity, excellent selectivity, rapid response/recovery, and low detection limit down to 0.1 ppm. The excellent sensing performance of the sensor with UV activation could be attributed to the photocatalytic oxidation of ethanol on the surface of the ZnO film, the planar film structure with high utilizing efficiency of UV light, high electron mobility, and a good surface/volume ratio of of ZnO film with a relatively rough and porous surface.
Energy Harvesting Hybrid Acoustic-Optical Underwater Wireless Sensor Networks Localization
Authors: Saeed Nasir , Celik Abdulkadir , Al-Naffouri Tareq Y. , Alouini Mohamed-Slim
Published: December 2017

Underwater wireless technologies demand to transmit at higher data rate for ocean exploration. Currently, large coverage is achieved by acoustic sensor networks with low data rate, high cost, high latency, high power consumption, and negative impact on marine mammals. Meanwhile, optical communication for underwater networks has the advantage of the higher data rate albeit for limited communication distances. Moreover, energy consumption is another major problem for underwater sensor networks, due to limited battery power and difficulty in replacing or recharging the battery of a sensor node. The ultimate solution to this problem is to add energy harvesting capability to the acoustic-optical sensor nodes. Localization of underwater sensor networks is of utmost importance because the data collected from underwater sensor nodes is useful only if the location of the nodes is known. Therefore, a novel localization technique for energy harvesting hybrid acoustic-optical underwater wireless sensor networks (AO-UWSNs) is proposed. AO-UWSN employs optical communication for higher data rate at a short transmission distance and employs acoustic communication for low data rate and long transmission distance. A hybrid received signal strength (RSS) based localization technique is proposed to localize the nodes in AO-UWSNs. The proposed technique combines the noisy RSS based measurements from acoustic communication and optical communication and estimates the final locations of acoustic-optical sensor nodes. A weighted multiple observations paradigm is proposed for hybrid estimated distances to suppress the noisy observations and give more importance to the accurate observations. Furthermore, the closed form solution for Cramer-Rao lower bound (CRLB) is derived for localization accuracy of the proposed technique.
Multisensor Capacitance Probes for Simultaneously Monitoring Rice Field Soil-Water-Crop-Ambient Conditions
Authors: Brinkhoff James , Hornbuckle John , Dowling Thomas
Published: December 2017

Multisensor capacitance probes (MCPs) have traditionally been used for soil moisture monitoring and irrigation scheduling. This paper presents a new application of these probes, namely the simultaneous monitoring of ponded water level, soil moisture, and temperature profile, conditions which are particularly important for rice crops in temperate growing regions and for rice grown with prolonged periods of drying. WiFi-based loggers are used to concurrently collect the data from the MCPs and ultrasonic distance sensors (giving an independent reading of water depth). Models are fit to MCP water depth vs volumetric water content (VWC) characteristics from laboratory measurements, variability from probe-to-probe is assessed, and the methodology is verified using measurements from a rice field throughout a growing season. The root-mean-squared error of the water depth calculated from MCP VWC over the rice growing season was 6.6 mm. MCPs are used to simultaneously monitor ponded water depth, soil moisture content when ponded water is drained, and temperatures in root, water, crop and ambient zones. The insulation effect of ponded water against cold-temperature effects is demonstrated with low and high water levels. The developed approach offers advantages in gaining the full soil-plant-atmosphere continuum in a single robust sensor.
Synergistic Use of Gold Nanoparticles (AuNPs) and “Capillary Enzyme-Linked Immunosorbent Assay (ELISA)” for High Sensitivity and Fast Assays
Authors: Kim Wan-Joong , Cho Hyo , Jeong Bongjin , Byun Sangwon , Huh JaeDoo , Kim Young
Published: December 2017

Using gold nanoparticles (AuNPs) on “capillary enzyme-linked immunosorbent assay (ELISA)”, we produced highly sensitive and rapid assays, which are the major attributes for point-of-care applications. First, in order to understand the size effect of AuNPs, AuNPs of varying diameters (5 nm, 10 nm, 15 nm, 20 nm, 30 nm, and 50 nm) conjugated with Horseradish Peroxidase (HRP)-labeled anti-C reactive protein (antiCRP) (AuNP•antiCRP-HRP) were used for well-plate ELISA. AuNP of 10 nm produced the largest optical density, enabling detection of 0.1 ng/mL of CRP with only 30 s of incubation, in contrast to 10 ng/mL for the ELISA run in the absence of AuNP. Then, AuNP of 10 nm conjugated with antiCRP-HRP (AuNP•antiCRP-HRP) was used for “capillary ELISA” to detect as low as 0.1 ng/mL of CRP. Also, kinetic study on both 96-well plates and in a capillary tube using antiCRP-HRP or AuNP•antiCRP-HRP showed a synergistic effect between AuNP and the capillary system, in which the fastest assay was observed from the “AuNP capillary ELISA”, with its maximum absorbance reaching 2.5 min, while the slowest was the typical well-plate ELISA with its maximum absorbance reaching in 13.5 min.
Correct Use of Three-Point Seatbelt by Pregnant Occupants
Authors: Acar B. , Edwards Alix , Aldah Mostafa
Published: December 2017

The largest cause of accidental death and placental abruption in pregnancy is automobile collisions. Lives can be saved by correct use of the three-point seatbelt during pregnancy. Human interaction is essential for correct use of seatbelts. The objective of this study is to investigate pregnant women’s use of correct shoulder section together with correct lap section as advised by obstetricians and highway experts and to identify the most common seatbelt misuse during pregnancy. An international web survey was conducted in five languages for this study. 1931 pregnant women reported their use of seatbelts and how they position the shoulder and lap sections of their seatbelts. Special attention was paid to distinguish between ‘partly correct’ and ‘correct’ seatbelt positioning. The questionnaire responses are used to determine the magnitude of every combination of the correct and incorrect shoulder and lap section of the seatbelt positioning during pregnancy. Results show that seatbelt usage in pregnancy is generally high in the world. However, the correct use of the entire seatbelt is very low, at only 4.3% of all respondents. 40.8% of the respondents use the shoulder portion of the belt correctly, whilst a 13.2% use the lap section correctly. The most common misuse is ‘across abdomen’ or ‘not using the seatbelt at all’, and both pose danger to pregnant women and their fetuses. Correct use of three point seatbelts is a challenge during pregnancy. We recommend that the media, medical community, and automotive industry provide targeted information about correct seatbelt use during pregnancy and accident databases include ‘correct seatbelt use’ information in crash statistics.
Chiral Recognition by DNA-Immobilized TLC Plate
Authors: Yamada Masanori , Inoue Mami
Published: December 2017

DNA-immobilized silica gel TLC plate (DNA-TLC plate) by coating a mixture of double-stranded DNA and silica gel on a glass plate was stable in common organic solvents, such as alcohol, acetone, chloroform, and ethyl acetate. DNA-TLC plate showed different Rf values for the L- and D-form acidic amino acids, such as aspartic acid and glutamic acid. The chiral recognition of an acidic amino acid by the DNA-TLC was related to the interaction between the nucleic acid base, particularly guanine (G) and cytosine (C), and the amino acid. Furthermore, the DNA-TLC plate indicated the recognition of a chiral metal complex, such as the tris(1,10-phenanthroline)ruthenium(II) ([Ru(phen)3]2+) salt, which has Λ- and Δ-forms. Therefore, the double-stranded DNA-TLC plate may have the potential to be utilized as a chiral separation material for amino acids, peptides, and a metal complex with a chiral property.
The (In)Significance of Socio-Demographic Factors as Possible Determinants of Vietnamese Social Scientists’ Contribution-Adjusted Productivity: Preliminary Results from 2008–2017 Scopus Data
Authors: Vuong Thu-Trang , Nguyen Hong , Ho Tung , Ho Toan , Vuong Quan-Hoang
Published: December 2017

As collaboration has become widespread in academia, and the number of authors per article has increased, the publication count is no longer an accurate indicator of scientific output in many cases. To overcome this limitation, this study defined and computed a relative count of publications called ‘CP’ (credit-based contribution points), based on the sequence-determines-credit (SDC) method, which takes into account the level of contribution of each author. Analyses were done on a sample of 410 Vietnamese social scientists whose publications were indexed in the Scopus database during 2008–2017. The results showed that the average CP of Vietnamese researchers in the field of social sciences and humanities is very low: more than 88% of authors have a CP less than five over a span 10 years. Researchers with a higher CP were mostly 40–50 years old; however, even for this sub-group, the mean CP was only 3.07. Multiple attributes of first-authorship—including knowledge, research skills, and critical thinking—could boost the CP by a ratio of 1:1.06. There is no evidence of gender differences in productivity, however, there is a regional difference. These findings offer significant insights into the education system in regard to science and technology, namely policy implications for science funding and management strategies for research funds.
Impact of Farmers’ Training Centres on Household Income: Evidence from Propensity Score Matching in Eastern Ethiopia
Authors: Wordofa Muluken , Sassi Maria
Published: December 2017

In developing countries, agricultural advisory services (AASs) are regarded as a key component of economic development strategies in terms of improving productivity and livelihoods. Nevertheless, there is a dearth of empirical evidence on the impact of AASs in general and the Farmers’ Training Centres (FTCs) in particular. In this article, we employ the propensity score matching procedure to estimate the impact of an FTC-based training on household farm income in eastern Ethiopia. The result indicates a significant average gain of annual farm income by participants of the training, ranging from Birr 9557 to Birr 10,388 per household.
Spatial Heterogeneity of Typical Ecosystem Services and Their Relationships in Different Ecological–Functional Zones in Beijing–Tianjin–Hebei Region, China
Authors: Xie Zhen , Gao Yang , Li Chao , Zhou Jian , Zhang Tianzhu
Published: December 2017

Recognizing changes in ecosystem services (ES) and their relationships is the basis of achieving sustainable regional development. Regional collaborative development has become the core strategy of the development of the Beijing–Tianjin–Hebei (BTH) region. However, sub regions have different ecological changes and relationships. Here, we quantify and map ES, including water yield, sediment retention, carbon sequestration and grain productive capacity in 2000, 2005, 2010 and 2015, using several biophysical models and explore the relationships of spatial correction, trade-offs and synergies among multiple ES in different spatial scales. Results across the four years show that the quality and variation tendency of ES from each region are spatially heterogeneous. The relationship between ES that are not significant in the entire region shows different correlations in individual ecological–functional zones. From the perspective of regional disparity, the effect of land use factor and correlative mechanisms among ES are analyzed. To observe the spatiotemporal variations and relationships of ES in individual regions, land use management policies are proposed on the basis of the results of the relationships among ES.