bluuebunny/crossref_metadata_2025 huggingface dataset:
A Novel Thin-Film Nanocomposite Nanofiltration Membrane by Incorporating 3D Hyperbranched Polymer Functionalized 2D Graphene Oxide
Authors: Xie Quanling , Zhang Shishen , Ma Hanjun , Shao Wenyao , Gong Xiao , Hong Zhuan
Published: November 2018

In order to develop a high-performance thin-film nanocomposite (TFN) nanofiltration (NF) membrane, the functionalized graphene-based nanomaterial (GO-HBE-COOH) was synthesized by combining two-dimensional graphene oxide (GO) with a three-dimensional hyperbranched polymer, which was used as the novel nanofiller and successfully embedded into the polypiperazine-amide (PPA) active layers on polysulfone (PSU) substrates via interfacial polymerization (IP) process. The resultant NF membranes were characterized using ATR-FTIR, SEM, and AFM, while their performance was evaluated in terms of water flux, salt rejection, antifouling ability, and chlorine resistance. The influence of GO-HBE-COOH concentration on the morphologies, properties, and performance of TFN NF membranes was investigated. With the addition of 60 ppm GO-HBE-COOH, the TFN-GHC-60 NF membrane exhibited the optimal water flux without a sacrifice of the salt rejection. It was found that the introduction of GO-HBE-COOH nanosheets favored the formation of a thinner and smoother nanocomposite active layer with an enhanced hydrophilicity and negative charge. As a result, TFN NF membranes demonstrated a superior permeaselectivity, antifouling ability, and chlorine resistance over the conventional PPA thin-film composite (TFC) membranes.
Synergistic Effect of Halloysite Nanotubes and Glycerol on the Physical Properties of Fish Gelatin Films
Authors: Qiang Xiaohu , Zhou Songyi , Zhang Zhuo , Quan Qiling , Huang Dajian
Published: November 2018

Fish gelatin (FG)/glycerol (GE)/halloysite (HT) composite films were prepared by casting method. The morphology of the composite films was observed by scanning electron microscopy (SEM). The effects of HT and GE addition on the mechanical properties, water resistance and optical properties of the composites were investigated. Results showed that with increasing GE content, the elongation at composite breaks increased significantly, but their tensile strength (TS) and water resistance decreased. SEM results showed that GE can partly promote HT dispersion in composites. TS and water resistance also increased with the addition of HTs. Well-dispersed HTs in the FG matrix decreased the moisture uptake and water solubility of the composites. All films showed a transparency higher than 80% across the visible light region (400–800 nm), thereby indicating that light transmittance of the resulting nanocomposites was slightly affected by GE and HTs.
Self-Structuring in Water of Polyamidoamino Acids with Hydrophobic Side Chains Deriving from Natural α-Amino Acids
Authors: Lazzari Federica , Manfredi Amedea , Alongi Jenny , Mendichi Raniero , Ganazzoli Fabio , Raffaini Giuseppina , Ferruti Paolo , Ranucci Elisabetta
Published: November 2018

This paper reports on synthesis, acid-base properties and self-structuring in water of chiral polyamidoamino acids (PAACs) obtained by polyaddition of N,N′-methylenebisacrylamide with l-alanine, l-valine and l-leucine (M-l-Ala, M-l-Val, M-l-Leu) with potential for selective interactions with biomolecules. The polymers maintained the acid-base properties of amino acids. In water, the circular dichroism spectra of PAACs revealed pH-dependent structuring in the range 3–11 and in the wavelength interval 200–280 nm. Taking as reference the values at pH 3, the differential molar ellipticities were plotted in the pH interval 3–11. Sigmoidal curves were obtained presenting inflection points at pH 8.1, 6.8 and 7.3 for M-l-Ala, M-l-Val and M-l-Leu, respectively, corresponding to the amine half-ionization. Theoretical modeling showed that PAACs assumed stable folded conformations. Intramolecular interactions led to transoid arrangements of the main chain reminiscent of protein hairpin motif. Oligomers with ten repeat units had simulated gyration radii consistent with the hydrodynamic radii obtained by dynamic light scattering.
Paraquat-Mediated Oxidative Stress in Anopheles gambiae Mosquitoes Is Regulated by An Endoplasmic Reticulum (ER) Stress Response
Authors: Tarimo Brian , Law Henry , Tao Dingyin , Pastrana-Mena Rebecca , Kanzok Stefan , Buza Joram , Dinglasan Rhoel
Published: November 2018

Paraquat is a potent superoxide (O2−)-inducing agent that is capable of inducing an oxidative imbalance in the mosquito midgut. This oxidative imbalance can super-stress the malaria parasite, leading to arrested development in the mosquito midgut and reduced transmission. While several studies have explored the effect of paraquat on malaria parasites, a fundamental understanding of the mosquito response to this compound remains unknown. Here, we quantified the mosquito midgut proteomic response to a paraquat-laced sugar meal, and found that An. gambiae midguts were enriched in proteins that are indicative of cells under endoplasmic reticulum (ER) stress. We also carried out qRT-PCR analyses for nine prominent thioredoxin (Trx) and glutathione (GSH)-dependent genes in mosquito midguts post P. falciparum blood meal ingestion to evaluate the concordance between transcripts and proteins under different oxidative stress conditions. Our data revealed an absence of significant upregulation in the Trx and GSH-dependent genes following infected blood meal ingestion. These data suggest that the intrinsic tolerance of the mosquito midgut to paraquat-mediated oxidative stress is through an ER stress response. These data indicate that mosquitoes have at least two divergent pathways of managing the oxidative stress that is induced by exogenous compounds, and outline the potential application of paraquat-like drugs to act selectively against malaria parasite development in mosquito midguts, thereby blocking mosquito-to-human transmission.
Contemplative Practice, Doxographies, and the Construction of Tibetan Buddhism: Nupchen Sangyé Yeshé and The Lamp for the Eye in Meditation
Authors: Lopez Manuel
Published: November 2018

In this article, I would like to reframe our understanding of the role played by doxographies or classification of views (Skt. siddhānta, Ch. panjiao 判教, Tib. grub mtha’) in the Buddhist tradition as it pertained to Tibetan attempts at defining and organizing the diversity of Buddhist contemplative practices that made their way into Tibet since the introduction of Buddhism to the Tibetan plateau in the seventh century, all the way up to the collapse of the Tibetan Empire in the ninth century. In order to do that, this article focuses on one such doxography, the Lamp for the Eye in Meditation (bsam gtan mig sgron), composed in the 10th century by the Tibetan scholar Nupchen Sangyé Yeshé. The first part of the article will place Nupchen’s text in the larger historical and intellectual context of the literary genre of doxographies in India, China, and Tibet. The second part of the article will argue that Nupchen used the doxographical genre not only as a vehicle for organizing and articulating doctrinal and contemplative diversity, but also as a tool for the construction of a new and original system of Tibetan Buddhist practice known as ‘the Great Perfection’ (rdzogs chen). Finally, and as a small homage to the recent passing of the great religious studies scholar Jonathan Z. Smith, I would also like to reflect on the importance that the issues of definition, comparison, and classification—central concerns of Nupchen’s as well as of Smith’s works—have in creating and articulating religious difference.
A Vision-Based Neural Network Controller for the Autonomous Landing of a Quadrotor on Moving Targets
Authors: Almeshal Abdullah M. , Alenezi Mohammad R.
Published: November 2018

Time constraints is the most critical factor that faces the first responders’ teams for search and rescue operations during the aftermath of natural disasters and hazardous areas. The utilization of robotic solutions to speed up search missions would help save the lives of humans who are in need of help as quickly as possible. With such a human-robot collaboration, by using autonomous robotic solutions, the first response team will be able to locate the causalities and possible victims in order to be able to drop emergency kits at their locations. This paper presents a design of vision-based neural network controller for the autonomous landing of a quadrotor on fixed and moving targets for Maritime Search and Rescue applications. The proposed controller does not require prior information about the target location and depends entirely on the vision system to estimate the target positions. Simulations of the proposed controller are presented using ROS Gazebo environment and are validated experimentally in the laboratory using a Parrot AR Drone system. The simulation and experimental results show the successful control of the quadrotor in autonomously landing on both fixed and moving landing platforms.
Introduction of the Double-Differenced Ambiguity Resolution into Precise Point Positioning
Authors: Li Haojun , Xiao Jingxin , Zhang Shoujian , Zhou Jin , Wang Jiexian
Published: November 2018

According to the advantages of the precise point positioning (PPP) and the double-differenced (DD) model based algorithm, a new method for the integration of DD integer ambiguity resolution into PPP is presented. This method uses the undifferenced ambiguity estimated with PPP computation and the DD ambiguity generated from the DD model based algorithm to realize the PPP ambiguity fixing. In the presented method, the selection of the undifferenced ambiguity bases on the ratio test of the DD ambiguity and the ratio values based weight is used in PPP processing. This ensures the quality of the used undifferenced ambiguity. To validate the presented method, two experiments are implemented using the ten days (11 to 20 August 2014) data from local and regional reference stations and the moved two receivers. The results of the presented strategy show that improvements are achieved in all three coordinate components. The 1-h, 2-h, and 4-h PPP results indicate that the mean relative improvements were about 19%, 18%, and 15% for north, east, and up components. These results also show that prominent improvements of 29%, 31%, and 25% for north, east, and up components were obtained when the ratio values based weight was used. The application of the presented method in the displacement monitoring was implemented with the experiment and it showed that the PPP estimation computed with the presented strategy benefits local or regional displacement monitoring and improves the detecting ability for displacement.
Confronting Soil Moisture Dynamics from the ORCHIDEE Land Surface Model With the ESA-CCI Product: Perspectives for Data Assimilation
Authors: Raoult Nina , Delorme Bertrand , Ottlé Catherine , Peylin Philippe , Bastrikov Vladislav , Maugis Pascal , Polcher Jan
Published: November 2018

Soil moisture plays a key role in water, carbon and energy exchanges between the land surface and the atmosphere. Therefore, a better representation of this variable in the Land-Surface Models (LSMs) used in climate modelling could significantly reduce the uncertainties associated with future climate predictions. In this study, the ESA-CCI soil moisture (SM) combined product (v4.2) has been confronted to the simulated top-first layers/cms of the ORCHIDEE LSM (the continental part of the IPSL Earth System Model) for the years 2008-2016, to evaluate its potential to improve the model using data assimilation techniques. The ESA-CCI data are first rescaled to match the climatology of the model and the signal representative depth is selected. Results are found to be relatively consistent over the first 20 cm of the model. Strong correlations found between the model and the ESA-CCI product show that ORCHIDEE can adequately reproduce the observed SM dynamics. As well as considering two different atmospheric forcings to drive the model, we consider two different model parameterizations related to the soil resistance to evaporation. The correlation metric is shown to be more sensitive to the choice of meteorological forcing than to the choice of model parameterization. Therefore, the metric is not optimal in highlighting structural deficiencies in the model. In contrast, the temporal autocorrelation metric is shown to be more sensitive to this model parameterization, making the metric a potential candidate for future data assimilation experiments.
Radiometric Cross-Calibration of Tiangong-2 MWI Visible/NIR Channels over Aquatic Environments using MODIS
Authors: Zhou Qu , Tian Liqiao , Li Jian , Song Qingjun , Li Wenkai
Published: November 2018

The Moderate-Resolution Wide-Wavelength Imager (MWI), onboard the Tiangong-2 (TG-2) Space Lab, is an experimental satellite sensor designed for the next-generation Chinese ocean color satellites. The MWI imagery is not sufficiently radiometrically calibrated, and therefore, the cross-calibration is urgently needed to provide high quality ocean color products for MWI observations. We proposed a simple and effective cross-calibration scheme for MWI data using well calibrated Moderate Resolution Imaging Spectroradiometer (MODIS) imagery over aquatic environments. The path radiance of the MWI was estimated using the quasi-synchronized MODIS images as well as the MODIS Rayleigh and aerosol look up tables (LUTs) from SeaWiFS Data Analysis System 7.4 (SeaDAS 7.4). The results showed that the coefficients of determination (R2) of the calibration coefficients were larger than 0.97, with sufficient matched areas to perform cross-calibration for MWI. Compared with the simulated Top of Atmosphere (TOA) radiance using synchronized MODIS images, all errors calculated with the calibration coefficients retrieved in this paper were less than 5.2%, and lower than the lab calibrated coefficients. The Rayleigh-corrected reflectance (ρrc), remote sensing reflectance (Rrs) and total suspended matter (TSM) products of MWI, MODIS and the Geostationary Ocean Color Imager (GOCI) images for Taihu Lake in China were compared. The distribution of ρrc of MWI, MODIS and GOCI agreed well, except for band 667 nm of MODIS, which might have been saturated in relatively turbid waters. Besides, the Rrs used to retrieve TSM among MWI, MODIS and GOCI was also consistent. The root mean square errors (RMSE), mean biases (MB) and mean ratios (MR) between MWI Rrs and MODIS Rrs (or GOCI Rrs) were less than 0.20 sr−1, 5.52% and within 1 ± 0.023, respectively. In addition, the derived TSM from MWI and GOCI also agreed with a R2 of 0.90, MB of 13.75%, MR of 0.97 and RMSE of 9.43 mg/L. Cross-calibration coefficients retrieved in this paper will contribute to quantitative applications of MWI. This method can be extended easily to other similar ocean color satellite missions.
Comparison of Pre-Event VHR Optical Data and Post-Event PolSAR Data to Investigate Damage Caused by the 2011 Japan Tsunami in Built-Up Areas
Authors: Jung Minyoung , Yeom Junho , Kim Yongil
Published: November 2018

Combining pre-disaster optical and post-disaster synthetic aperture radar (SAR) satellite data is essential for the timely damage investigation because the availability of data in a disaster area is usually limited. This article proposes a novel method to assess damage in urban areas by analyzing combined pre-disaster very high resolution (VHR) optical data and post-disaster polarimetric SAR (PolSAR) data, which has rarely been used in previous research because the two data have extremely different characteristics. To overcome these differences and effectively compare VHR optical data and PolSAR data, a technique to simulate polarization orientation angles (POAs) in built-up areas was developed using building orientations extracted from VHR optical data. The POA is an intrinsic parameter of PolSAR data and has a physical relationship with building orientation. A damage level indicator was also proposed, based on the consideration of diminished homogeneity of POA values by damaged buildings. The indicator is the difference between directional dispersions of the pre and post-disaster POA values. Damage assessment in urban areas was conducted by using the indicator calculated with the simulated pre-disaster POAs from VHR optical data and the derived post-disaster PolSAR POAs. The proposed method was validated on the case study of the 2011 tsunami in Japan using pre-disaster KOMPSAT-2 data and post-disaster ALOS/PALSAR-1 data. The experimental results demonstrated that the proposed method accurately simulated the POAs with a root mean square error (RMSE) value of 2.761° and successfully measured the level of damage in built-up areas. The proposed method can facilitate efficient and fast damage assessment in built-up areas by comparing pre-disaster VHR optical data and post-disaster PolSAR data.
A Novel Hybrid of a Fading Filter and an Extreme Learning Machine for GPS/INS during GPS Outages
Authors: Wang Di , Xu Xiaosu , Zhu Yongyun
Published: November 2018

In this paper, a novel algorithm based on the combination of a fading filter (FF) and an extreme learning machine (ELM) is presented for Global Positioning System/Inertial Navigation System (GPS/INS) integrated navigation systems. In order to increase the filtering accuracy of the model, a variable fading factor fading filter based on the fading factor is proposed. It adjusts the fading factor by the ratio of the estimated covariance before and after the moment which proves to have excellent performance in our experiment. An extreme learning machine based on a Fourier orthogonal basis function is introduced that considers the deterioration of the accuracy of the navigation system during GPS outages and has a higher positioning accuracy and faster learning speed than the typical neural network learning algorithm. In the end, a simulation and real road test are performed to verify the effectiveness of this algorithm. The results show that the accuracy of the fading filter based on a variable fading factor is clearly improved, and the proposed improved ELM algorithm can provide position corrections during GPS outages more effectively than the other algorithms (ELM and the traditional radial basis function neural network).
Dynamic Pose Estimation Using Multiple RGB-D Cameras
Authors: Hong Sungjin , Kim Yejin
Published: November 2018

Human poses are difficult to estimate due to the complicated body structure and the self-occlusion problem. In this paper, we introduce a marker-less system for human pose estimation by detecting and tracking key body parts, namely the head, hands, and feet. Given color and depth images captured by multiple red, green, blue, and depth (RGB-D) cameras, our system constructs a graph model with segmented regions from each camera and detects the key body parts as a set of extreme points based on accumulative geodesic distances in the graph. During the search process, local detection using a supervised learning model is utilized to match local body features. A final set of extreme points is selected with a voting scheme and tracked with physical constraints from the unified data received from the multiple cameras. During the tracking process, a Kalman filter-based method is introduced to reduce positional noises and to recover from a failure of tracking extremes. Our system shows an average of 87% accuracy against the commercial system, which outperforms the previous multi-Kinects system, and can be applied to recognize a human action or to synthesize a motion sequence from a few key poses using a small set of extremes as input data.
A Multisensor Fusion Method for Tool Condition Monitoring in Milling
Authors: Zhou Yuqing , Xue Wei
Published: November 2018

Tool fault diagnosis in numerical control (NC) machines plays a significant role in ensuring manufacturing quality. Tool condition monitoring (TCM) based on multisensors can provide more information related to tool condition, but it can also increase the risk that effective information is overwhelmed by redundant information. Thus, the method of obtaining the most effective feature information from multisensor signals is currently a hot topic. However, most of the current feature selection methods take into account the correlation between the feature parameters and the tool state and do not analyze the influence of feature parameters on prediction accuracy. In this paper, a multisensor global feature extraction method for TCM in the milling process is researched. Several statistical parameters in the time, frequency, and time–frequency (Wavelet packet transform) domains of multiple sensors are selected as an alternative parameter set. The monitoring model is executed by a Kernel-based extreme learning Machine (KELM), and a modified genetic algorithm (GA) is applied in order to search the optimal parameter combinations in a two-objective optimization model to achieve the highest prediction precision. The experimental results show that the proposed method outperforms the Pearson’s correlation coefficient (PCC) based, minimal redundancy and maximal relevance (mRMR) based, and Principal component analysis (PCA)-based feature selection methods.
Predicting Profile Soil Properties with Reflectance Spectra via Bayesian Covariate-Assisted External Parameter Orthogonalization
Authors: S. Veum Kristen , A. Parker Paul , A. Sudduth Kenneth , H. Holan Scott
Published: November 2018

In situ, diffuse reflectance spectroscopy (DRS) profile soil sensors have the potential to provide both rapid and high-resolution prediction of multiple soil properties for precision agriculture, soil health assessment, and other applications related to environmental protection and agronomic sustainability. However, the effects of soil moisture, other environmental factors, and artefacts of the in-field spectral data collection process often hamper the utility of in situ DRS data. Various processing and modeling techniques have been developed to overcome these challenges, including external parameter orthogonalization (EPO) transformation of the spectra. In addition, Bayesian modeling approaches may improve prediction over traditional partial least squares (PLS) regression. The objectives of this study were to predict soil organic carbon (SOC), total nitrogen (TN), and texture fractions using a large, regional dataset of in situ profile DRS spectra and compare the performance of (1) traditional PLS analysis, (2) PLS on EPO-transformed spectra (PLS-EPO), (3) PLS-EPO with the Bayesian Lasso (PLS-EPO-BL), and (4) covariate-assisted PLS-EPO-BL models. In this study, soil cores and in situ profile DRS spectrometer scans were obtained to ~1 m depth from 22 fields across Missouri and Indiana, USA. In the laboratory, soil cores were split by horizon, air-dried, and sieved (<2 mm) for a total of 708 samples. Soil properties were measured and DRS spectra were collected on these air-dried soil samples. The data were randomly split into training (n = 308), testing (n = 200), and EPO calibration (n = 200) sets, and soil textural class was used as the categorical covariate in the Bayesian models. Model performance was evaluated using the root mean square error of prediction (RMSEP). For the prediction of soil properties using a model trained on dry spectra and tested on field moist spectra, the PLS-EPO transformation dramatically improved model performance relative to PLS alone, reducing RMSEP by 66% and 53% for SOC and TN, respectively, and by 76%, 91%, and 87% for clay, silt, and sand, respectively. The addition of the Bayesian Lasso further reduced RMSEP by 4–11% across soil properties, and the categorical covariate reduced RMSEP by another 2–9%. Overall, this study illustrates the strength of the combination of EPO spectral transformation paired with Bayesian modeling techniques to overcome environmental factors and in-field data collection artefacts when using in situ DRS data, and highlights the potential for in-field DRS spectroscopy as a tool for rapid, high-resolution prediction of soil properties.
A Novel Method for Breath Detection via Stepped-Frequency Continuous Wave Ultra-Wideband (SFCW UWB) Radars Based on Operational Bandwidth Segmentation
Authors: Lv Hao , Jiao Teng , Zhang Yang , Liang Fulai , Qi Fugui , Wang Jianqi
Published: November 2018

Human being detection via ultra-wideband (UWB) radars has shown great prospects in many areas, such as biomedicine, military operation, public security, emergency rescue, and so on. When a person stays stationary, the main feature that separates him/her from surroundings is the movement of chest wall due to breath. There have been many algorithms developed for breath detection while using UWB radars. However, those algorithms were almost based on a basic scheme that focused on processing in the time dimension of UWB data. They did not utilize the benefits from the wide operational bandwidth of UWB radars to show potential superiority over those narrowband systems such as a continuous wave (CW) Doppler radar. In this paper, a breath detection method was proposed based on operational bandwidth segmentation. A basic theoretical model was firstly introduced, indicating that characteristics of breath signals contained in UWB echoes were consistent among the operational frequencies, while those of clutters were not. So, the method divided a set of UWB echo data into a number of subsets, each of which corresponded to a sub-band within the operational bandwidth of the UWB radar. Thus information about the operational frequency is provided for subsequent processing. With the aid of the information, a breath enhancement algorithm was developed mainly by averaging the segmented UWB data along the operational frequency. The algorithm’s performance was verified by data measured by a stepped-frequency CW (SFCW) UWB radar. The experimental results showed that the algorithm performed better than that without the segmentation. They also showed its feasibility for fast detection of breath based on a short duration of data. Moreover, the method’s potential for target identification and impulse-radio (IR) UWB radar was investigated. In summary, the method provides a new processing scheme for UWB radars when they are used for breath detection. With this scheme, the UWB radars have a benefit of greater flexibility in data processing over those narrowband radars, and thus will perform more effectively and efficiently in practical applications.
Optimized Gateway Placement for Interference Cancellation in Transmit-Only LPWA Networks
Authors: Tian Hongxian , Weitnauer Mary Ann , Nyengele Gedeon
Published: November 2018

We study the placement of gateways in a low-power wide-area sensor network, when the gateways perform interference cancellation and when the model of the residual error of interference cancellation is proportional to the power of the packet being canceled. For the case of two sensor nodes sending packets that collide, by which we mean overlap in time, we deduce a symmetric two-crescent region wherein a gateway can decode both collided packets. For a large network of many sensors and multiple gateways, we propose two greedy algorithms to optimize the locations of the gateways. Simulation results show that the gateway placements by our algorithms achieve lower average contention, which means higher packet delivery ratio in the same conditions, than when gateways are naively placed, for several area distributions of sensors.
Ultrasonic Sensing and Actuation in Laminate Structures Using Bondline-Embedded d35 Piezoelectric Sensors
Authors: Altammar Hussain , Dhingra Anoop , Salowitz Nathan
Published: November 2018

Ultrasonic systems employing embedded piezoelectric transducers have seen increased interest in recent years. The ability to sense, actuate, and analyze the wave propagation modes in engineering structures has been fundamental to the advancement of ultrasonic structural health monitoring (SHM). This paper presents a study into the sensing and actuation properties of shear-mode (d35) piezoelectric transducers made of lead zirconate titanate (PZT) that are internally embedded in the bondline of laminate structures. The manuscript presents analytical analysis, finite element simulation, and experimental validation building from an individual piezoelectric element to a full laminate structure. The validated model was then used to perform a parametric study into the effects of d35 PZT transducer size on the strength of actuation and sensing output signal. The selectivity of d35 PZT sensors was also investigated by generating multiple wave modes in the laminate structure and inspecting the output signals. The d35 PZT sensors were found to selectively detect only certain modes of the wave propagation providing a fundamental hardware filter that could be employed to simplify signal analysis and processing. The results of this study indicate that d35 PZTs embedded in the bondline have multiple properties that can potentially be employed for ultrasonic SHM.
Indium Nitrite (InN)-Based Ultrasensitive and Selective Ammonia Sensor Using an External Silicone Oil Filter for Medical Application
Authors: Rai Sujeet Kumar , Kao Kun-Wei , Gwo Shanjgr , Agarwal Ashish , Lin Wei Da , Yeh J. Andrew
Published: November 2018

Ammonia is an essential biomarker for noninvasive diagnosis of liver malfunction. Therefore, selective detection of ammonia is essential for medical application. Here, we demonstrate a portable device to selectively detect sub-ppm ammonia gas. The presented gas sensor is composed of a Pt coating on top of an ultrathin Indium nitrite (InN) epilayer with a lower detection limit of 0.2 ppm, at operating temperature of 200 °C, and detection time of 1 min. The sensor connected with the external filter of nonpolar 500 CS silicone oil to diagnose liver malfunction. The absorption of 0.7 ppm acetone and 0.4 ppm ammonia gas in 10 cc silicone oil is 80% (0.56 ppm) and 21.11% (0.084 ppm), respectively, with a flow rate of 10 cc/min at 25 °C. The absorption of acetone gas is 6.66-fold higher as compared to ammonia gas. The percentage variation in response for 0.7 ppm ammonia and 0.7 ppm acetone with and without silicone oil on InN sensor is 17.5% and 4%, and 22.5%, and 14% respectively. Furthermore, the percentage variation in response for 0.7 ppm ammonia gas with silicone oil on InN sensor is 4.3-fold higher than that of 0.7 ppm acetone. The results show that the InN sensor is suitable for diagnosis of liver malfunction.
Triple-Band Dual-Sense Circularly Polarized Hybrid Dielectric Resonator Antenna
Authors: Altaf Amir , Seo Munkyo
Published: November 2018

In this paper, a triple-band dual-sense circularly polarized (CP) hybrid dielectric resonator antenna is proposed. A modified hexagonal dielectric resonator (DR) is top-loaded with a square microstrip ring (SMR). A vertical-tapered-strip connected to a 50- Ω microstrip line is used to excite the proposed antenna. It is found that the lower and central CP bands correspond to left-handed circular polarization and are produced by the TM 11 and TE 111 modes of the SMR and modified hexagonal DR, respectively. The upper CP band is formed by the combination of the quasi-TM 21 mode of the SMR and quasi-TE 111 mode of the DR that exhibits right-handed circular polarization. The measurement results of the fabricated prototype show triple-band response for |S 11 | < −10 dB with impedance bandwidths (IBWs) of 17.4% (1.75–2.03 GHz), 28.13% (2.23–2.96 GHz), and 2.97% (3.65–3.76 GHz) in the lower, central, and upper bands, respectively. The measured 3 dB axial ratio bandwidths lying within −10 dB IBWs are 3.69% (1.86–1.93 GHz), 5.46% (2.67–2.82 GHz), and 2.15% (3.68–3.76 GHz) along with the peak gains of 5 dBic, 5.28 dBic, and 2.36 dBic in the lower, central, and upper bands, respectively.
Correction Method for the Observed Global Navigation Satellite System Ultra-Rapid Orbit Based on Dilution of Precision Values
Authors: Wang Qianxin , Hu Chao , Mao Ya
Published: November 2018

For ultra-rapid orbits provided by the Global Navigation Satellite System (GNSS), the key parameters, accuracy and timeliness, must be taken into consideration in real-time and near real-time applications. However, insufficient observations in later epochs appear to generate low accuracy in observed orbits, for which a correlation between the Dilution of Precision (DOP) of the orbit parameters and their accuracy is found. To correct the observed GNSS ultra-rapid orbit, a correction method based on the DOP values is proposed by building the function models between DOP values and the orbit accuracy. With 10-day orbit determination experiments, the results show that the observed ultra-rapid-orbit errors, generated by insufficient observations, can be corrected by 12–22% for the last three hours of the observed orbits. Moreover, considering the timeliness constraints in ultra-rapid-orbit determination, a DOP amplification factor is defined to weight the contribution of each tracking station and optimize the station distribution in the orbit determination procedure. Finally, six schemes are designed to verify the method and strategy in determining the ultra-rapid orbit based on one-month observations. The orbit accuracy is found to decrease by 1.27–6.34 cm with increasing amplification factor from 5–20%. Thus, the observed ultra-orbit correction method proposed is ideal when considering accuracy and timeliness in ultra-rapid orbit determination.
Spin Rate Effects in a Micromachined Electrostatically Suspended Gyroscope
Authors: Sun Boqian , Wang Shunyue , Tan Yidong , Liu Yunfeng , Han Fengtian
Published: November 2018

Spin rate of a high-speed spinning-rotor gyroscope will make a significant impact on angular rate sensor performances such as the scale factor, resolution, measurement range, and bias stability. This paper presents the spin rate effects on performance indicators of a microelectromechanical systems (MEMS) gyroscope where a free-spinning rotor is electrostatically suspended in an evacuated vacuum cavity and functions as a dual-axis angular rate sensor. Theoretical models of the scale factor and measurement range of such a spinning-rotor gyroscope are derived. The experimental results indicate that the measured scale factors at different settings of the spin rate match well with the theoretical predication. In order to separate the disturbance component of the rotation control loop on the gyroscope output, a testing strategy is proposed by operating the gyroscope at different spin rates. Experimental results on a prototype gyroscope show that the squared drive voltage generated by the rotation control loop is approximately proportional to the noise of the gyroscope output. It was further investigated that an improved performance of such spinning-rotor gyroscopes can be achieved by operating the gyroscope rotor at an optimal spin rate.
Measurements and Accuracy Evaluation of a Strapdown Marine Gravimeter Based on Inertial Navigation
Authors: Wang Wei , Gao Jinyao , Li Dongming , Zhang Tao , Luo Xiaowen , Wang Jinling
Published: November 2018

The strapdown gravimetry system uses the combination of an Inertial Measuring Unit (IMU) and a Global Navigation Satellite System (GNSS) to measure the Earth’s gravity field. Due to limited accuracies of IMU and GNSS, early strapdown gravimetry systems were more often used in airborne surveys, but less used in marine surveys. We developed a strapdown inertial navigation system (SINS), the Sea-Air Gravimeter-2Marine (SAG-2M), using novel IMU components, whose accuracy was further improved with the application of Precise Point Positioning (PPP) and enhanced algorithm, making it possible to be used in marine gravity survey. The testing results of the SAG-2M were compared to those of the Lacoste and Romberg S-129 gravimeter on the same ship in the South China Sea basin. The cruise lasted for 50 days, during which 134 effective gravity profiles were measured, resulting in 174 crossover points. The results showed that, for the SAG-2M, the root mean square (RMS) crossover points were 1.35 mGal before difference adjustment and 0.69 mGal after difference adjustment; for the S-129 gravimeter, they were 5.62 mGal and 0.95 mGal, correspondingly. In calm sea conditions, the results of the two systems were relatively consistent at all wavelengths. However, in rough sea conditions, since the SAG-2M was not affected by the cross-coupling effect, its data demonstrated less high-frequency jump. A physical platform adopted in SAG-2M can further make the transition data effective when the ship is turning around. Therefore, SAG-2M was able to improve the proportion of valid data and the efficiency of data post-processing for measurements taken during the cruise. The testing results indicate that in terms of accuracy and efficiency in the marine gravity survey, SAG-2M is better than S-129. In addition, as the miniaturization and precision of inertial components are developing continuously, SAG-2M also shows great potential in miniaturization.
High-Efficiency Automatic Recharging Mechanism for Cleaning Robot Using Multi-Sensor
Authors: Chang Ching-Lung , Chang Chuan-Yu , Tang Zhi-Yuan , Chen Shuo-Tsung
Published: November 2018

Cleaning robot has the highest penetration rate among the service robots. This paper proposes a high-efficiency mechanism for an intelligent cleaning robot automatically returns to charging in a short time when the power is insufficient. The proposed mechanism initially combines the robot’s own motor encoder with neural network linear regression to calculate the moving distance and rotation angle for the location estimation of the robot itself. At the same time, a self-rotating camera is applied to scan the number of infrared spots on the docking station to find the location of the docking station so that the cleaning robot returns to charging properly in two stages, existing infrared range and extended infrared range. In addition, six-axis acceleration and ultrasound are both applied to deal with the angle error that is caused by collision. Experimental results show that the proposed recharging mechanism significantly improves the efficiency of recharging.
Torus Pairwise Disjoint-Path Routing
Authors: Bossard Antoine , Kaneko Keiichi
Published: November 2018

Modern supercomputers include hundreds of thousands of processors and they are thus massively parallel systems. The interconnection network of a system is in charge of mutually connecting these processors. Recently, the torus has become a very popular interconnection network topology. For example, the Fujitsu K, IBM Blue Gene/L, IBM Blue Gene/P, and Cray Titan supercomputers all rely on this topology. The pairwise disjoint-path routing problem in a torus network is addressed in this paper. This fundamental problem consists of the selection of mutually vertex disjoint paths between given vertex pairs. Proposing a solution to this problem has critical implications, such as increased system dependability and more efficient data transfers, and provides concrete implementation of green and sustainable computing as well as security, privacy, and trust, for instance, for the Internet of Things (IoT). Then, the correctness and complexities of the proposed routing algorithm are formally established. Precisely, in an n-dimensional k-ary torus ( n < k , k ≥ 5 ), the proposed algorithm connects c ( c ≤ n ) vertex pairs with mutually vertex-disjoint paths of lengths at most 2 k ( c − 1 ) + n ⌊ k / 2 ⌋ , and the worst-case time complexity of the algorithm is O ( n c 4 ) . Finally, empirical evaluation of the proposed algorithm is conducted in order to inspect its practical behavior.
Proactive Coverage Area Decisions Based on Data Field for Drone Base Station Deployment
Authors: Hu Bo , Wang Chuan’an , Chen Shanzhi , Wang Lei , Yang Hanzhang
Published: November 2018

Using the drone base station (DBS) to alleviate the network coverage supply-demand mismatch is an attractive issue. Found in DBS-assisted cellular mobile networks, the deployment of DBSs to cope with the dynamic load requirements is an important problem. The authors propose a proactive DBS deployment method to enhance the DBS deployment flexibility based on network traffic. The proposed scheme uses potential value and minimum distance to decide the areas that most need to be covered, which are named as proactive coverage areas (PCAs), whereby the DBSs are assigned to cover those PCAs. Meanwhile, when the number of required DBSs is determined, the energy consumption is related to the coverage radius and the altitude of DBSs. Therefore, the proposed method further investigates the on-demand coverage radius and then obtains the altitude of DBSs. Simulations show that the proposed proactive DBS deployment method provides better coverage performance with a significant complexity reduction.
A Deep Learning Approach on Building Detection from Unmanned Aerial Vehicle-Based Images in Riverbank Monitoring
Authors: Boonpook Wuttichai , Tan Yumin , Ye Yinghua , Torteeka Peerapong , Torsri Kritanai , Dong Shengxian
Published: November 2018

Buildings along riverbanks are likely to be affected by rising water levels, therefore the acquisition of accurate building information has great importance not only for riverbank environmental protection but also for dealing with emergency cases like flooding. UAV-based photographs are flexible and cloud-free compared to satellite images and can provide very high-resolution images up to centimeter level, while there exist great challenges in quickly and accurately detecting and extracting building from UAV images because there are usually too many details and distortions on UAV images. In this paper, a deep learning (DL)-based approach is proposed for more accurately extracting building information, in which the network architecture, SegNet, is used in the semantic segmentation after the network training on a completely labeled UAV image dataset covering multi-dimension urban settlement appearances along a riverbank area in Chongqing. The experiment results show that an excellent performance has been obtained in the detection of buildings from untrained locations with an average overall accuracy more than 90%. To verify the generality and advantage of the proposed method, the procedure is further evaluated by training and testing with another two open standard datasets which have a variety of building patterns and styles, and the final overall accuracies of building extraction are more than 93% and 95%, respectively.
Fast Phase-Only Positioning with Triple-Frequency GPS
Authors: Wang Kan , Chen Pei , Teunissen Peter
Published: November 2018

In this contribution, we study the phase-only ambiguity resolution and positioning performance of GPS for short baselines. It is well known that instantaneous (single-epoch) ambiguity resolution is possible when both phase and code (pseudorange) data are used. This requires, however, a benign multipath environment due to the severe effects multipath has on the code measurements. With phase-only processing, one would be free from such severe effects, be it that phase-only processing requires a change in receiver-satellite geometry, as a consequence of which it cannot be done instantaneously. It is thus of interest to know how much change in the relative receiver-satellite geometry is needed to achieve successful phase-only ambiguity resolution with correspondingly high precision baseline solutions. In this contribution, we study the two-epoch phase-only performance of single-, dual-, and triple-frequency GPS for varying time spans from 60 s down to 1 s. We demonstrate, empirically as well as formally, that fast phase-only very-precise positioning is indeed possible, and we explain the circumstances that make this possible. The formal analyses are also performed for a large area including Australia, a part of Asia, the Indian Ocean, and the Pacific Ocean. We remark that in this contribution "phase-only" refers to phase-only measurements in the observation model, while the code data are thus only used to compute the approximate values needed for linearizing the observation equations.
Evaluating the Performance of Functionalized Carbon Structures with Integrated Optical Fiber Sensors under Practical Conditions
Authors: Bremer Kort , Alwis Lourdes S. M. , Weigand Frank , Kuhne Michael , Zheng Yulong , Krüger Marco , Helbig Reinhard , Roth Bernhard
Published: November 2018

An Optical Frequency Domain Reflectometry (OFDR) based fiber optic sensor scheme “embedded” in concrete for the purpose of structural health monitoring (SHM) of carbon concrete composites (C3) is presented. The design, while strengthening the concrete structure, also aims to monitor common SHM parameters such as strain and cracks. This was achieved by weaving the carbon fiber together with optical fiber, based on a specialized technique that uses an embroidery setup where both the carbon and optical fiber are woven on a water dissolvable polymer substrate. The performance of the sensing scheme was characterized in-situ utilizing the OFDR based technique and the results presented. The sensors embedded on a custom made concrete block were subjected to varying strain via a three point bending test to destruction and the results discussed. The intended dual-achievement of the scheme thus proposed in SHM and strengthening the C3 is demonstrated. The suitability of the OFDR scheme for C3 is combined with a fibre Bragg grating (FBG)-based approach, and discussed in detail.
Performance Analysis of NDT-based Graph SLAM for Autonomous Vehicle in Diverse Typical Driving Scenarios of Hong Kong
Authors: Wen Weisong , Hsu Li-Ta , Zhang Guohao
Published: November 2018

Robust and lane-level positioning is essential for autonomous vehicles. As an irreplaceable sensor, Light detection and ranging (LiDAR) can provide continuous and high-frequency pose estimation by means of mapping, on condition that enough environment features are available. The error of mapping can accumulate over time. Therefore, LiDAR is usually integrated with other sensors. In diverse urban scenarios, the environment feature availability relies heavily on the traffic (moving and static objects) and the degree of urbanization. Common LiDAR-based simultaneous localization and mapping (SLAM) demonstrations tend to be studied in light traffic and less urbanized area. However, its performance can be severely challenged in deep urbanized cities, such as Hong Kong, Tokyo, and New York with dense traffic and tall buildings. This paper proposes to analyze the performance of standalone NDT-based graph SLAM and its reliability estimation in diverse urban scenarios to further evaluate the relationship between the performance of LiDAR-based SLAM and scenario conditions. The normal distribution transform (NDT) is employed to calculate the transformation between frames of point clouds. Then, the LiDAR odometry is performed based on the calculated continuous transformation. The state-of-the-art graph-based optimization is used to integrate the LiDAR odometry measurements to implement optimization. The 3D building models are generated and the definition of the degree of urbanization based on Skyplot is proposed. Experiments are implemented in different scenarios with different degrees of urbanization and traffic conditions. The results show that the performance of the LiDAR-based SLAM using NDT is strongly related to the traffic condition and degree of urbanization. The best performance is achieved in the sparse area with normal traffic and the worse performance is obtained in dense urban area with 3D positioning error (summation of horizontal and vertical) gradients of 0.024 m/s and 0.189 m/s, respectively. The analyzed results can be a comprehensive benchmark for evaluating the performance of standalone NDT-based graph SLAM in diverse scenarios which is significant for multi-sensor fusion of autonomous vehicle.