bluuebunny/crossref_metadata_2025 huggingface dataset:
Nanoparticles-Modified Chemical Sensor Fabricated on a Flexible Polymer Substrate for Cadmium(II) Detection
Authors: Wang Nan , Kanhere Elgar , Miao Jianmin , Triantafyllou Michael
Published: June 2018

This paper presents the development of a chemical sensor which was microfabricated on top of liquid crystal polymer (LCP) substrate. As a result of the unique material properties of LCP, the sensor showed favorable flexibility as well as operational reliability. These features demonstrate potential for integration of the sensor into automated sensing vehicles to achieve real-time detection. The sensor consists of a gold working electrode, a silver/silver chloride reference electrode, and a gold counter electrode. The working electrode of the sensor was further modified with bismuth nanoparticles and Nafion. The modified sensor exhibited a significantly enhanced sensing capability toward cadmium metal ion (Cd(II)) in comparison to the unmodified one. The effects of deposition potential and deposition time on the sensing performance of the sensor were extensively investigated through electrochemical experiments. With optimized parameters, the sensor was capable of quantifying Cd(II) in the concentration range of 0.3 to 25 µg/L. The minimum Cd(II) concentration detected by the sensor was 0.06 µg/L under quiescent deposition. The obtained results suggest that the proposed sensor has a great potential to be deployed for in-situ Cd(II) determination.
High-Performance Polyimide Filaments and Composites Improved by O2 Plasma Treatment
Authors: Lin Fangbing , Li Wei , Tang Yusi , Shao Huiqi , Su Chuanli , Jiang Jinhua , Chen Nanliang
Published: June 2018

Interface issues urgently need to be addressed in high-performance fiber reinforced composites. In this study, different periods of O2 plasma treatment are proposed to modify twist-free polyimide (PI) filaments to improve hydrophilicity and mechanical and interfacial properties. Feeding O2 produces chemically active particles to modify the filament surface via chemical reactions and physical etching. According to the X-ray photoelectron spectroscopy (XPS) results, the PI filaments exhibit an 87.16% increase in O/C atomic ratio and a 135.71% increase in the C–O functional group after 180 s O2 plasma treatment. The atomic force microscope (AFM) results show that the root mean square roughness (Rq) of the treated PI filaments increases by 105.34%, from 38.41 to 78.87 nm. Owing to the increased surface oxygenic functional groups and roughness after O2 plasma treatment, the contact angle between treated PI filaments and water reduces drastically from the pristine state of 105.08° to 56.15°. The O2 plasma treated PI filaments also demonstrate better mechanical properties than the pristine PI filaments. Moreover, after O2 plasma treatment, the adhesion between PI filaments and poly(amic acid) (PAA) is enhanced, and the tensile strength of the polyimide/poly(amic acid) (PI/PAA) self-reinforced composites increases from 136 to 234 MPa, even causing the failure mode of the composite changes from adhesive failure to partly cohesive failure.
Systematic Design and Evaluation of an Extraction Process for Traditionally Used Herbal Medicine on the Example of Hawthorn (Crataegus monogyna JACQ.)
Authors: Sixt Maximilian , Strube Jochen
Published: June 2018

Traditionally used herbal medicines are deep in the consciousness of patients for the treatment of only minor diseases by self-medication. However, manufacturers of herbal medicinal products suffer from major problems such as increasing market pressure by e.g., the food supplement sector, increasing regulations, and costs of production. Moreover, due to more stringent regulation and approval processes, innovation is hardly observed, and the methods used in process development are outdated. Therefore, this study aims to provide an approach based on modern process engineering concepts and including predictive process modelling and simulation for the extraction of traditional herbal medicines as complex extracts. The commonly used solvent-based percolation is critically assessed and compared to the so-called pressurized hot water extraction (PHWE) as a new possible alternative to replace organic solvents. In the study a systematic process design for the extraction of hawthorn (Crataegus monogyna JACQ.) is shown. While for traditional percolation the solvent is optimized to a mixture of ethanol and water (70/30 v/v), the PHWE is run at a temperature of 90 °C. The extracts of various harvest batches are compared to a commercially available product based on a chromatographic fingerprint. For the first time, natural batch variability was successfully incorporated into the physico-chemical process modelling concept. An economic feasibility study reveals that the PHWE is the best choice not only from a technical point of view but also from economic aspects.
Modelling of a Naphtha Recovery Unit (NRU) with Implications for Process Optimization
Authors: Du Jiawei , Cluett William R.
Published: June 2018

The naphtha recovery unit (NRU) is an integral part of the processes used in the oil sands industry for bitumen extraction. The principle role of the NRU is to recover naphtha from the tailings for reuse in this process. This process is energy-intensive, and environmental guidelines for naphtha recovery must be met. Steady-state models for the NRU system are developed in this paper using two different approaches. The first approach is a statistical, data-based modelling approach where linear regression models have been developed using Minitab® from plant data collected during a performance test. The second approach involves the development of a first-principles model in Aspen Plus® based on the NRU process flow diagram. A novel refinement to this latter model, called “withdraw and remix”, is proposed based on comparing actual plant data to model predictions around the two units used to separate water and naphtha. The models developed in this paper suggest some interesting ideas for the further optimization of the process, in that it may be possible to achieve the required naphtha recovery using less energy. More plant tests are required to validate these ideas.
Editorial for Special Issue: 2017 Plant Proteomics
Authors: Jamet Elisabeth , Santoni Véronique
Published: June 2018

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Cross-Scale Correlation between In Situ Measurements of Canopy Gap Fraction and Landsat-Derived Vegetation Indices with Implications for Monitoring the Seasonal Phenology in Tropical Forests Using MODIS Data
Authors: Cuba Nicholas , Rogan John , Lawrence Deborah , Williams Christopher
Published: June 2018

Deciduousness in dry tropical forests results in substantial seasonal changes to canopy gap fractions. The characterization of such structural properties over large areas is necessary for understanding energy and nutrient distribution within forest ecosystems. However, a spatial extrapolation of measurements from relatively few, spatially-concentrated field observations can yield estimated values that have questionable accuracy and precision at regional scales. This paper uses linear regression models to compare measurements of canopy gap fraction from in situ digital cover photography in the dry tropical forest of the Southern Yucatán, Mexico, to measurements of seasonal vegetation change based on three vegetation indices—the Normalized Difference Vegetation Index (NDVI), two-band Enhanced Vegetation Index (EVI2), and the Normalized Difference Water Index (NDWI)—derived from Landsat-7 ETM+ and Landsat-8 Operational Land Imager (OLI) data to gauge the ability of standardized combinations of multispectral reflectance data to accurately describe the intensity of deciduousness that occurs during the dry season. Discrete observations are compared, as well as spatially summarized values at coarser spatial scales. Model R2 values are greater at coarse spatial scales for all vegetation indices. Models of in situ measurements of gap fraction and Landsat NDWI normalized seasonal change exhibit stronger correlation than do models that feature NDVI or EVI2 (R² = 0.751 and Mean Absolute Error = 0.04 after aggregation, R² = 0.552 and MAE = 0.07 for observation-level data). Based on its comparatively strong correlation with field observations, NDWI is adapted to a Moderate Resolution Imaging Spectroradiometer (MODIS) time series and used for spatial extrapolation and the monitoring of canopy conditions. NDWI values derived from MODIS data are regressed against Tropical Rainforest Measuring Misson (TRMM) rainfall data over the period 2000–2011, and the regression results are compared to those of a prior study that used regression to explain the variation of a MODIS EVI using TRMM rainfall data. A MODIS NDWI time series reveals stronger correlation (R² = 0.48 in deciduous forests) with TRMM accumulated (three-month) rainfall data than a MODIS EVI time series. The results indicate that an NDWI time series can accurately describe a variability of canopy leaf abundance during the dry season and could be an alternative basis of long-term monitoring of season phenology in a dry tropical forest.
Urban Change Detection Based on Dempster–Shafer Theory for Multitemporal Very High-Resolution Imagery
Authors: Luo Hui , Liu Chong , Wu Chen , Guo Xian
Published: June 2018

Fusing multiple change detection results has great potentials in dealing with the spectral variability in multitemporal very high-resolution (VHR) remote sensing images. However, it is difficult to solve the problem of uncertainty, which mainly includes the inaccuracy of each candidate change map and the conflicts between different results. Dempster–Shafer theory (D–S) is an effective method to model uncertainties and combine multiple evidences. Therefore, in this paper, we proposed an urban change detection method for VHR images by fusing multiple change detection methods with D–S evidence theory. Change vector analysis (CVA), iteratively reweighted multivariate alteration detection (IRMAD), and iterative slow feature analysis (ISFA) were utilized to obtain the candidate change maps. The final change detection result is generated by fusing the three evidences with D–S evidence theory and a segmentation object map. The experiment indicates that the proposed method can obtain the best performance in detection rate, false alarm rate, and comprehensive indicators.
Assessment of Root Zone Soil Moisture Estimations from SMAP, SMOS and MODIS Observations
Authors: Pablos Miriam , González-Zamora Ángel , Sánchez Nilda , Martínez-Fernández José
Published: June 2018

In this study, six satellite-based root zone soil moisture (RZSM) estimates from March 2015 to December 2016 were evaluated both temporally and spatially. The first two were the Soil Moisture Active Passive (SMAP) and the Soil Moisture and Ocean Salinity (SMOS) L4 RZSM products. The other four were obtained through the Soil Water Index (SWI) approach, which embedded surface soil moisture (SSM). The SMOS-Barcelona Expert Center (BEC) L4 SSM product and the apparent thermal inertia (ATI)-derived SSM from the Moderate Resolution Imaging Spectroradiometer (MODIS) data were used as SSM datasets. In the temporal analysis, the RZSM estimates were compared to in situ RZSM from 14 stations of the Soil Moisture Measurements Station Network of the University of Salamanca (REMEDHUS). Regarding the spatial assessment, the resulting RZSM maps of the Iberian Peninsula were compared between them. All RZSM values followed the temporal evolution of the ground-based measurements well, although SMOS and MODIS showed underestimation while SMAP displayed overestimation. The good results obtained from MODIS ATI are notable, notwithstanding they were not estimated through microwave radiometry. A very high agreement was found in terms of spatial patterns for the whole Iberian Peninsula except for the extreme north area, which is dominated by high mountains and dense forests.
Evaluation of the First Year of Operational Sentinel-2A Data for Retrieval of Suspended Solids in Medium- to High-Turbidity Waters
Authors: Caballero Isabel , Steinmetz François , Navarro Gabriel
Published: June 2018

In this study, we apply high-resolution Sentinel-2A imagery to assist in the monitoring of the southwestern Spanish coast during its first year of data. The aim is to test suitability of MultiSpectral Imager (MSI) at higher resolution (10 m) for mapping Total Suspended Solids (TSS). Several field campaigns are carried out to collect TSS at three different sites in the Guadalquivir estuary, Cadiz Bay and Conil port. A regional multi-conditional remote sensing algorithm with a switching method that automatically selects the most sensitive TSS vs. water reflectance relationship is developed to estimate TSS concentration while avoiding saturation effects. An existing semi-analytical algorithm is calibrated by means of a cross-validation procedure based on both red 664 nm (r = 0.8, NRMSE of 25.06%) and near-infrared (NIR) 865 nm (r = 0.98, NRMSE of 10.28%) parts of the spectrum, showing the MSI sensor’s great potential to estimate TSS even though it was not designed for aquatic remote sensing. The first year of data reveals improved monitoring along the coastal region at unprecedented resolution with accuracy to detect the Estuarine Turbidity Maximum (ETM). ACOLITE and POLYMER Atmospheric Correction strategies are applied over this coastal region (no in-situ data on water reflectance). The results confirm that the flexible POLYMER algorithm can address intense sun-glint effects. These findings encourage further research of water quality studies relying on both operational Sentinel-2A and Sentinel-2B, with great implications to improve the understanding of turbid coastal and inland water environments.
Growth of Retrogressive Thaw Slumps in the Noatak Valley, Alaska, 2010–2016, Measured by Airborne Photogrammetry
Authors: Swanson David K. , Nolan Matt
Published: June 2018

We monitored the growth of 22 retrogressive thaw slumps (RTS), dramatic erosion features associated with thaw of permafrost, in the Noatak Valley of northern Alaska using high-resolution structure-from-motion digital photogrammetry. We created time-series of 3–6 Digital Elevation Models (DEMs) and orthophoto mosaics during the time period from 2010–2016 at each slump, using high-resolution digital single-lens reflex (SLR) photographs taken from airplanes or helicopters. DEMs created using airborne GPS camera locations were adequate to detect elevations changes as small as 10 to 15 cm. Measurements made on these DEMs and orthophotographs showed slump growth rates of up to 38 m yr−1, with the fastest rates on slumps with scarps of moderate height (1 to 4 m) exposing Pleistocene glacial ice. Most of the slumps grew at constant or declining rates during the study, apparently as a result of the slumps encountering more gentle topography as they expanded upslope. Sedimentation was predominantly on the slump floor within 40 m of the active scarp, and the zone of accumulation migrated upslope with the scarp, away from adjacent water bodies. This study demonstrates that low-cost cameras coupled with airborne GPS and no ground control are suitable for monitoring geomorphic change on the order of decimeters and are a powerful tool for monitoring in remote settings.
Initial Assessment of Precise Point Positioning with LEO Enhanced Global Navigation Satellite Systems (LeGNSS)
Authors: Ge Haibo , Li Bofeng , Ge Maorong , Zang Nan , Nie Liangwei , Shen Yunzhong , Schuh Harald
Published: June 2018

The main challenge of precise point positioning (PPP) applications is the long convergence time of typically a half hour, or even more, to achieve centimeter accuracy. Even when the multi-constellation is involved and ambiguity resolution is implemented, it still requires about ten minutes. It is becoming a hot spot to incorporate the low Earth orbit (LEO) satellite constellation for enhancing the Global Navigation Satellite System (GNSS), named here as LEO-enhanced GNSS (LeGNSS). In this system, the LEO satellites cannot only receive GNSS signals, but also serve as GNSS satellites by transmitting similar navigation signals to the ground users, but with higher signal strength and much faster geometric change due to their low altitude. As a result, the convergence time of PPP is expected to be shortened to a few minutes, or even seconds. Simulation software is developed to simulate GNSS and LEO observations for ground stations taking into account tropospheric delay, satellite clock errors, observation noises, as well as other error sources. Then the number of visible satellites, the geometry dilution of precision (GDOP), and the convergence time of the kinematic mode of PPP are evaluated on a global scale compared to those of GNSS systems. The simulation results show that LeGNSS can decrease the PPP convergence to 5 min. If there are more LEO satellites included in the LeGNSS, it is expected that the initialization of PPP can be further shortened.
Lake Surface Water Temperature Derived from 35 Years of AVHRR Sensor Data for European Lakes
Authors: Lieberherr Gian , Wunderle Stefan
Published: June 2018

Lake surface water temperature (LSWT) is an important parameter with which to assess aquatic ecosystems and to study the lake’s response to climate change. The AVHRR archive of the University of Bern offers great potential to derive consistent LSWT data suited for the study of climate change and lake dynamics. To derive such a dataset, challenges such as orbit drift correction, non-water pixel detection, and homogenization had to be solved. The result is a dataset covering over 3.5 decades of spatial LSWT data for 26 European lakes. The validation against in-situ temperature data at 19 locations showed an uncertainty between ±0.8 K and ±2.0 K (standard deviation), depending on locations of the lakes. The long-term robustness of the dataset was confirmed by comparing in-situ and satellite derived temperature trends, which showed no significant difference. The final trend analysis showed significant LSWT warming trends at all locations (0.2 K/decade to 0.8 K/decade). A gradient of increasing trends from south-west to north-east of Europe was revealed. The strong intra-annual variability of trends indicates that single seasonal trends do not well represent the response of a lake to climate change, e.g., autumn trends are dominant in the north of Europe, whereas winter trends are dominant in the south. Intra-lake variability of trends indicates that trends at single in-situ stations do not necessarily represent the lake’s response. The LSWT dataset generated for this study gives some new and interesting insights into the response of European lakes to climate change during the last 36 years (1981–2016).
Investigations into Frost Flower Physical Characteristics and the C-Band Scattering Response
Authors: Isleifson Dustin , Galley Ryan J. , Firoozy Nariman , Landy Jack C. , Barber David G.
Published: June 2018

A dedicated study on the physical characteristics and C-band scattering response of frost-flower-covered sea ice was performed in an artificial sea ice mesocosm over a 36-h period in January 2017. Meteorological conditions were observed and recorded automatically at the facility when the sea ice grew and frost flowers formed while the C-band scattering measurements were conducted continuously over a range of incidence angles. Surface roughness was characterized using a LiDAR. During the experiment, frost flowers did not initially form on the extremely smooth ice surface even though suitable meteorological conditions prevailed during their development (low air temperature, low near-surface wind speed, and high near-surface relative humidity). This provides evidence that both the presence of (i) liquid brine at the surface and (ii) raised nodules as nucleation points are required to enable frost flower initiation. As the ice thickened, we observed that raised nodules gradually appeared, frost flowers formed, and flowers subsequently spread to cover the surface over a six-hour period. In contrast to previous experiments, the frost flower layer did not become visibly saturated with liquid brine. The C-band scattering measurements exhibited increases as high as 14.8 dB (vertical polarization) in response to the frost flower formation with low incidence angles (i.e., 25°) showing the largest dynamic range. Co-polarization ratios responded to the physical and thermodynamic changes associated with the frost flower formation process. Our results indicate that brine expulsion at the sea ice surface and frost flower salination can have substantial temporal variability, which can be detected by scatterometer time-series measurements. This work contributes towards the operational satellite image interpretation for Arctic waters by improving our understanding of the highly variable C-band microwave scattering properties of young sea ice types.
Landslide Identification and Monitoring along the Jinsha River Catchment (Wudongde Reservoir Area), China, Using the InSAR Method
Authors: Zhao Chaoying , Kang Ya , Zhang Qin , Lu Zhong , Li Bin
Published: June 2018

Landslide identification and monitoring are two significant research aspects for landslide analysis. In addition, landslide mode deduction is key for the prevention of landslide hazards. Surface deformation results with different scales can serve for different landslide analysis. L-band synthetic aperture radar (SAR) data calculated with Interferometric Point Target Analysis (IPTA) are first employed to detect potential landslides at the catchment-scale Wudongde reservoir area. Twenty-two active landslides are identified and mapped over more than 2500 square kilometers. Then, for one typical landslide, Jinpingzi landslide, its spatiotemporal deformation characteristics are analyzed with the small baseline subsets (SBAS) interferometric synthetic aperture radar (InSAR) technique. High-precision surface deformation results are obtained by comparing with in-situ georobot measurements. The spatial deformation pattern reveals the different stabilities among five different sections of Jinpingzi landslide. InSAR results for Section II of Jinpingzi landslide show that this active landslide is controlled by two boundaries and geological structure, and its different landslide deformation magnitudes at different sections on the surface companying with borehole deformation reveals the pull-type landslide mode. Correlation between time series landslide motion and monthly precipitation, soil moisture inverted from SAR intensity images and water level fluctuations suggests that heavy rainfall is the main trigger factor, and the maximum deformation of the landslide was highly consistent with the peak precipitation with a time lag of about 1 to 2 months, which gives us important guidelines to mitigate and prevent this kind of hazard.
Remote Sensing Image Compression Based on Direction Lifting-Based Block Transform with Content-Driven Quadtree Coding Adaptively
Authors: Shi Cuiping , Wang Liguo , Zhang Junping , Miao Fengjuan , He Peng
Published: June 2018

Due to the limitations of storage and transmission in remote sensing scenarios, lossy compression techniques have been commonly considered for remote sensing images. Inspired by the latest development in image coding techniques, we present in this paper a new compression framework, which combines the directional adaptive lifting partitioned block transform (DAL-PBT) with content-driven quadtree codec with optimized truncation (CQOT). First, the DAL-PBT model is designed; it calculates the optimal prediction directions of each image block and performs the weighted directional adaptive interpolation during the process of directional lifting. Secondly, the CQOT method is proposed, which provides different scanning orders among and within blocks based on image content, and encodes those blocks with a quadtree codec with optimized truncation. The two phases are closely related: the former is devoted to image representation for preserving more directional information of remote sensing images, and the latter leverages adaptive scanning on the transformed image blocks to further improve coding efficiency. The proposed method supports various progressive transmission modes. Experimental results show that the proposed method outperforms not only the mainstream compression methods, such as JPEG2000 and CCSDS, but also, in terms of some evaluation indexes, some state-of-the-art compression methods presented recently.
Optimal Design of a Planar Textile Antenna for Industrial Scientific Medical (ISM) 2.4 GHz Wireless Body Area Networks (WBAN) with the CRO-SL Algorithm
Authors: Sánchez-Montero Rocío , Camacho-Gómez Carlos , López-Espí Pablo-Luís , Salcedo-Sanz Sancho
Published: June 2018

This paper proposes a low-profile textile-modified meander line Inverted-F Antenna (IFA) with variable width and spacing meanders, for Industrial Scientific Medical (ISM) 2.4-GHz Wireless Body Area Networks (WBAN), optimized with a novel metaheuristic algorithm. Specifically, a metaheuristic known as Coral Reefs Optimization with Substrate Layer (CRO-SL) is used to obtain an optimal antenna for sensor systems, which allows covering properly and resiliently the 2.4–2.45-GHz industrial scientific medical bandwidth. Flexible pad foam has been used to make the designed prototype with a 1.1-mm thickness. We have used a version of the algorithm that is able to combine different searching operators within a single population of solutions. This approach is ideal to deal with hard optimization problems, such as the design of the proposed meander line IFA. During the optimization phase with the CRO-SL, the proposed antenna has been simulated using CST Microwave Studio software, linked to the CRO-SL by means of MATLAB implementation and Visual Basic Applications (VBA) code. We fully describe the antenna design process, the adaptation of the CRO-SL approach to this problem and several practical aspects of the optimization and details on the algorithm’s performance. To validate the simulation results, we have constructed and measured two prototypes of the antenna, designed with the proposed algorithm. Several practical aspects such as sensitivity during the antenna manufacturing or the agreement between the simulated and constructed antenna are also detailed in the paper.
Smart Road Traffic Accidents Reduction Strategy Based on Intelligent Transportation Systems (TARS)
Authors: Aldegheishem Abdulaziz , Yasmeen Humera , Maryam Hafsa , Shah Munam Ali , Mehmood Amjad , Alrajeh Nabil , Song Houbing
Published: June 2018

Traffic accidents have become an important problem for governments, researchers and vehicle manufacturers over the last few decades. However, accidents are unfortunate and frequently occur on the road and cause death, damage to infrastructure, and health injuries. Therefore, there is a need to develop a protocol to avoid or prevent traffic accidents at the extreme level in order to reduce human loss. The aim of this research is to develop a new protocol, named as the Traffic Accidents Reduction Strategy (TARS), for Vehicular Ad-hoc NETworks (VANETs) to minimize the number of road accidents, decrease the death rate caused by road accidents, and for the successful deployment of the Intelligent Transportation System (ITS). We have run multiple simulations and the results showed that our proposed scheme has outperformed DBSR and POVRP routing protocols in terms of the Message Delivery Ratio (MDR), Message Loss Ratio (MLR), Average Delay, and Basic Safety Message.
Road Anomalies Detection System Evaluation
Authors: Silva Nuno , Shah Vaibhav , Soares João , Rodrigues Helena
Published: June 2018

Anomalies on road pavement cause discomfort to drivers and passengers, and may cause mechanical failure or even accidents. Governments spend millions of Euros every year on road maintenance, often causing traffic jams and congestion on urban roads on a daily basis. This paper analyses the difference between the deployment of a road anomalies detection and identification system in a “conditioned” and a real world setup, where the system performed worse compared to the “conditioned” setup. It also presents a system performance analysis based on the analysis of the training data sets; on the analysis of the attributes complexity, through the application of PCA techniques; and on the analysis of the attributes in the context of each anomaly type, using acceleration standard deviation attributes to observe how different anomalies classes are distributed in the Cartesian coordinates system. Overall, in this paper, we describe the main insights on road anomalies detection challenges to support the design and deployment of a new iteration of our system towards the deployment of a road anomaly detection service to provide information about roads condition to drivers and government entities.
Theoretical Analysis of a Microring Resonator Array with High Sensitivity and Large Dynamic Range Based on a Multi-Scale Technique
Authors: Mo Wenqin , Liu Huiyun , Jin Fang , Song Junlei , Dong Kaifeng
Published: June 2018

By using a multi-scale measurement technique, a high-sensitivity and large dynamic-range sensor array, which consisted of a single resonator and a series of cascaded resonators with a sensing ring and a reference ring, was modeled, and its transmission properties were investigated theoretically and numerically. We also set forth the principle of a multi-scale measurement technique based on the transmission spectrum of a resonator. This sensor array could have a nearly tenfold increase in sensitivity, and an improved dynamic range in an arrow wavelength range. The simulated results were in good agreement with the theoretical analysis.
Experimental Demonstration of Remote and Compact Imaging Spectrometer Based on Mobile Devices
Authors: Chen Jie , Cai Fuhong , He Rongxiao , He Sailing
Published: June 2018

Imaging spectrometers show great potential for environmental and biomedical sensing applications. Selfie sticks, which are tools used to take photographs or videos, have gained global popularity in recent years. Few people have connected these two objects, and few people have researched the application of imaging spectrometers to perform scientific monitoring in point-of-use scenarios. In this paper, we develop a compact imaging spectrometer (35 g in weight, 18 mm in diameter, and 72 mm in length) that can be equipped on a motorized selfie stick to perform remote sensing. We applied this system to perform environmental and facial remote sensing via motorized scanning. The absorption of chlorophyll and hemoglobin can be found in the reflectance spectra, indicating that our system can be used in urban greening monitoring and point-of-care testing. In addition, this compact imaging spectrometer was also easily attached to an underwater dome port and a quad-rotor unmanned aerial vehicle to perform underwater and airborne spectral detection. Our system offers a route toward mobile imaging spectrometers used in daily life.
UV Light Illumination Can Improve the Sensing Properties of LaFeO3 to Acetone Vapor
Authors: Zhang Heng , Qin Hongwei , Gao Chengyong , Zhou Guangjun , Chen Yanping , Hu Jifan
Published: June 2018

The synthesized LaFeO3 nanocrystalline sensor powders show positive response to sensing acetone vapor at 200 °C. The responses to acetone vapor (at 0.5, 1, 2, 5, 10 ppm) are 1.18, 1.22, 1.89, 3.2 and 7.83. To make the sensor operate at a lower optimum temperature, UV light illumination 365 nm is performed. Response of the sensor has a larger improvement under 365 nm UV light illumination than without it. The responses to acetone vapor (at 0.5, 1, 2, 5, 10 ppm) are 1.37, 1.85, 3.16, 8.32 and 14.1. Furthermore, the optimum operating temperature is reduced to 170 °C. As the relative humidity increases, the resistance and sensitivity of sensor are reduced. The sensor shows good selectivity toward acetone when compared with other gases. Since the detection of ultralow concentrations of acetone vapor is possible, the sensor can be used to preliminarily judge diabetes in the general public, as a high concentration of acetone is exhaled in breath of diabetic patients. The sensor shows a good stability, which is further enhanced under UV light illumination. The sensor shows better stability when under 365 nm UV light illumination. Whether under light illumination or not. The LaFeO3 material shows good performance as a sensor when exposed to acetone vapor.
A Systematic Survey on Sensor Failure Detection and Fault-Tolerance in Ambient Assisted Living
Authors: ElHady Nancy E. , Provost Julien
Published: June 2018

Ambient Assisted Living (AAL) systems aim to enable the elderly people to stay active and live independently into older age by monitoring their behaviour, provide the needed assistance and detect early signs of health status deterioration. Non-intrusive sensors are preferred by the elderly to be used for the monitoring purposes. However, false positive or negative triggers of those sensors could lead to a misleading interpretation of the status of the elderlies. This paper presents a systematic literature review of the sensor failure detection and fault tolerance in AAL equipped with non-intrusive, event-driven, binary sensors. The existing works are discussed, and the limitations and research gaps are highlighted.
Design and Modeling of a Test Bench for Dual-Motor Electric Drive Tracked Vehicles Based on a Dynamic Load Emulation Method
Authors: Wang Zhe , Lv Haoliang , Zhou Xiaojun , Chen Zhaomeng , Yang Yong
Published: June 2018

Dual-motor Electric Drive Tracked Vehicles (DDTVs) have attracted increasing attention due to their high transmission efficiency and economical fuel consumption. A test bench for the development and validation of new DDTV technologies is necessary and urgent. How to load the vehicle on a DDTV test bench exactly the same as on a real road is a crucial issue when designing the bench. This paper proposes a novel dynamic load emulation method to address this problem. The method adopts dual dynamometers to simulate both the road load and the inertia load that are imposed on the dual independent drive systems. The vehicle’s total inertia equivalent to the drive wheels is calculated with separate consideration of vehicle body, tracks and road wheels to obtain a more accurate inertia load. A speed tracking control strategy with feedforward compensation is implemented to control the dual dynamometers, so as to make the real-time dynamic load emulation possible. Additionally, a MATLAB/Simulink model of the test bench is built based on a dynamics analysis of the platform. Experiments are finally carried out on this test bench under different test conditions. The outcomes show that the proposed load emulation method is effective, and has good robustness and adaptability to complex driving conditions. Besides, the accuracy of the established test bench model is also demonstrated by comparing the results obtained from the simulation model and experiments.
Investigation of Gasochromic Rhodium Complexes Towards Their Reactivity to CO and Integration into an Optical Gas Sensor for Fire Gas Detection
Authors: Pannek Carolin , Tarantik Karina R. , Schmitt Katrin , Wöllenstein Jürgen
Published: June 2018

The detection of the toxic gas carbon monoxide (CO) in the low ppm range is required in different applications. We present a study of the reactivity of different gasochromic rhodium complexes towards the toxic gas carbon monoxide (CO). Therefore, variations of binuclear rhodium complexes with different ligands were prepared. They were characterized by FTIR spectroscopy, 1H NMR spectroscopy, and differential scanning calorimetry. All complexes are spectroscopically distinguishable and temperature stable up to at least 187 °C. The gasochromic behavior of all different compounds was tested. Therefore, the compounds were dissolved in toluene and exposed to 100 ppm CO for 10 min to investigate their gas sensitivity and reaction velocity. The changes in the transmission spectra were recorded by UV/vis spectroscopy. Furthermore, a significant influence of the solvent to the color dyes’ gasochromic reaction and behavior was observed. After characterization, one complex was transferred as sensing element into an optical gas sensor. Two different measurement principles (reflection- and waveguide-based) were built up and tested towards their capability as gasochromic CO sensors. Finally, different gas-dependent measurements were carried out.
GSOS-ELM: An RFID-Based Indoor Localization System Using GSO Method and Semi-Supervised Online Sequential ELM
Authors: Liu Fagui , Zhong Dexiang
Published: June 2018

With the rapid development of indoor positioning technology, radio frequency identification (RFID) technology has become the preferred solution due to its advantages of non-line-of-sight, non-contact and rapid identification. However, the accuracy of existing RFID indoor positioning algorithms is easily affected by the tag density and algorithm efficiency, and their environmental robustness is not strong enough. In this paper, we have introduced an RFID positioning algorithm based on the Glowworm Swarm Optimization (GSO) fused with semi-supervised online sequential extreme learning machine (SOS-ELM), which is called the GSOS-ELM algorithm. The GSOS-ELM algorithm automatically adjusts the regularization weights of the SOS-ELM algorithm through the GSO algorithm, so that it can quickly obtain the optimal regularization weights under different initial conditions; at the same time, the semi-supervised characteristics of the GSOS-ELM algorithm can significantly reduce the number of labeled reference tags and reduce the cost of positioning systems. In addition, the online learning phase of the GSOS-ELM algorithm can continuously update the system to perceive changes in the environment and resist the environmental interference. We have carried out experiments to study the influence factors and validate the performance, both the simulation and testbed experiment results show that compared with other algorithms, our proposed GSOS-ELM localization system can achieve more accurate positioning results and has certain adaptability to the changes of the environment.
A Correction Approach for the Inclined Array of Hydrophones in Synthetic Aperture Sonar
Authors: Wu Haoran , Tang Jinsong , Zhong Heping
Published: June 2018

A correction approach for the inclined array of hydrophones is proposed to prevent decline of the image quality in SAS. In this approach, the 2-way exact acoustic propagation path of the inclined array is transformed into the sum of a single root term and an offset term, where the single root term is the 2-way ideal propagation path and the offset term contains all errors cause by the inclined array. The correction for the offset term is separated into two steps: phase correction and delay correction. The phase correction is performed on the echo signal of each receiving hydrophone in the 2-D time domain by a phase multiplication and the delay correction is performed on the echo signal of each receiving hydrophone in the range frequency domain by a phase multiplication with a linear function of range frequency at the reference range. Finally, the effectiveness of the proposed approach is examined by the simulation experiments.
Hydrodynamic Tweezers: Trapping and Transportation in Microscale Using Vortex Induced by Oscillation of a Single Piezoelectric Actuator
Authors: Liu Xiaoming , Shi Qing , Lin Yuqing , Kojima Masaru , Mae Yasushi , Huang Qiang , Fukuda Toshio , Arai Tatsuo
Published: June 2018

The demand for a harmless noncontact trapping and transportation method in manipulation and measurement of biological micro objects waits to be met. In this paper, a novel micromanipulation method named “Hydrodynamic Tweezers” using the vortex induced by oscillating a single piezoelectric actuator is introduced. The piezoelectric actuator is set between a micropipette and a copper beam. Oscillating the actuator at a certain frequency causes the resonance of the copper beam and extend 1D straight oscillation of the piezoelectric actuator to 2D circular oscillation of the micropipette, which induces a micro vortex after putting the micropipette into fluid. The induced vortex featuring low pressure in its core area can trap the object nearby. A robotic micromanipulator is utilized to transport the trapped objects together with the micropipette. Experiments of trapping and transportation microbeads are carried out to characterize the key parameters. The results show that the trapping force can be controlled by adjusting peak-peak voltage of the sinusoidal voltage input into the piezoelectric actuator.
Fusion of Infrared Thermal Image and Visible Image for 3D Thermal Model Reconstruction Using Smartphone Sensors
Authors: Yang Ming-Der , Su Tung-Ching , Lin Hung-Yu
Published: June 2018

Thermal infrared imagery provides temperature information on target objects, and has been widely applied in non-destructive testing. However, thermal infrared imagery is not always able to display detailed textures of inspected objects, which hampers the understanding of geometric entities consisting of temperature information. Although some commercial software has been developed for 3D thermal model displays, the software requires the use of expensive specific thermal infrared sensors. This study proposes a cost-effective method for 3D thermal model reconstruction based on image-based modeling. Two smart phones and a low-cost thermal infrared camera are employed to acquire visible images and thermal images, respectively, that are fused for 3D thermal model reconstruction. The experiment results demonstrate that the proposed method is able to effectively reconstruct a 3D thermal model which extremely approximates its corresponding entity. The total computational time for the 3D thermal model reconstruction is intensive while generating dense points required for the creation of a geometric entity. Future work will improve the efficiency of the proposed method in order to expand its potential applications to in-time monitoring.
Digital Holography as Computer Vision Position Sensor with an Extended Range of Working Distances
Authors: Asmad Vergara Miguel , Jacquot Maxime , Laurent Guillaume , Sandoz Patrick
Published: June 2018

Standard computer vision methods are usually based on powerful contact-less measurement approaches but applications, especially at the micro-scale, are restricted by finite depth-of-field and fixed working distance of imaging devices. Digital holography is a lensless, indirect imaging method recording the optical wave diffracted by the object onto the image sensor. The object is reconstructed numerically by propagating the recorded wavefront backward. The object distance becomes a computation parameter that can be chosen arbitrarily and adjusted to match the object position. No refractive lens is used and usual depth-of-field and working distance limitations are replaced by less restrictive ones tied to the laser-source coherence-length and to the size and resolution of the camera sensor. This paper applies digital holography to artificial visual in-plane position sensing with an extra-large range-to-resolution ratio. The object is made of a pseudoperiodic pattern allowing a subpixel resolution as well as a supra field-of-observation displacement range. We demonstrate an in-plane resolution of 50 nm and 0.002deg. in X, Y and θ respectively, over a working distance range of more than 15 cm. The allowed workspace extends over 12×10×150mm3. Digital holography extends the field of application of computer vision by allowing an extra-large range of working distances inaccessible to refractive imaging systems.
Hydrogen Sulfide Gas Detection via Multivariate Optical Computing
Authors: Dai Bin , Jones Christopher Michael , Pearl Megan , Pelletier Mickey , Myrick Mickey
Published: June 2018

Hydrogen-sulfide gas is a toxic, colorless gas with a pungent odor that occurs naturally as a decomposition by-product. It is critical to monitor the concentration of hydrogen sulfide. Multivariate optical computing (MOC) is a method that can monitor analytes while minimizing responses to interferences. MOC is a technique by which an analogue calculation is performed entirely in the optical domain, which simplifies instrument design, prevents the drift of a calibration, and increases the strength and durability of spectroscopic instrumentation against physical perturbation when used for chemical detection and identification. This paper discusses the detection of hydrogen-sulfide gas in the ultraviolet (UV) spectral region in the presence of interfering gaseous species. A laboratory spectroscopic measurement system was set up to acquire the UV spectra of H2S and interference gas mixtures in high-pressure/high-temperature (HPHT) conditions. These spectra were used to guide the design and fabrication of a multivariate optical element (MOE), which has an expected measurement relative accuracy of 3.3% for H2S, with a concentration in the range of 0–150 nmol/mL. An MOC validation system with the MOE was used to test three samples of H2S and mercaptans mixtures under various pressures, and the relative accuracy of H2S measurement was determined to be 8.05%.
Future of Smart Cardiovascular Implants
Authors: Bussooa Anubhav , Neale Steven , Mercer John R.
Published: June 2018

Cardiovascular disease remains the leading cause of death in Western society. Recent technological advances have opened the opportunity of developing new and innovative smart stent devices that have advanced electrical properties that can improve diagnosis and even treatment of previously intractable conditions, such as central line access failure, atherosclerosis and reporting on vascular grafts for renal dialysis. Here we review the latest advances in the field of cardiovascular medical implants, providing a broad overview of the application of their use in the context of cardiovascular disease rather than an in-depth analysis of the current state of the art. We cover their powering, communication and the challenges faced in their fabrication. We focus specifically on those devices required to maintain vascular access such as ones used to treat arterial disease, a major source of heart attacks and strokes. We look forward to advances in these technologies in the future and their implementation to improve the human condition.
Insect-Mimetic Imaging System Based on a Microlens Array Fabricated by a Patterned-Layer Integrating Soft Lithography Process
Authors: Seo Minwon , Seo Jong-Mo , Cho Dong-il , Koo Kyo-in
Published: June 2018

In nature, arthropods have evolved to utilize a multiaperture vision system with a micro-optical structure which has advantages, such as compact size and wide-angle view, compared to that of a single-aperture vision system. In this paper, we present a multiaperture imaging system using a microlens array fabricated by a patterned-layer integrating soft lithography (PLISL) process which is based on a molding technique that can transfer three-dimensional structures and a gold screening layer simultaneously. The imaging system consists of a microlens array, a lens-adjusting jig, and a conventional (charge-coupled device) CCD image sensor. The microlens array has a light screening layer patterned among all the microlenses by the PLISL process to prevent light interference. The three-dimensionally printed jig adjusts the microlens array on the conventional CCD sensor for the focused image. The manufactured imaging system has a thin optic system and a large field-of-view of 100 degrees. The developed imaging system takes multiple images at once. To show its possible applications, multiple depth plane images were reconstructed based on the taken subimages with a single shot.