bluuebunny/crossref_metadata_2025 huggingface dataset:
Novel PEGylated Liposomes Enhance Immunostimulating Activity of isRNA
Authors: Kabilova Tatyana , Shmendel Elena , Gladkikh Daniil , Morozova Nina , Maslov Mikhail , Chernolovskaya Elena , Vlassov Valentin , Zenkova Marina
Published: November 2018

The performance of cationic liposomes for delivery of therapeutic nucleic acids in vivo can be improved and specifically tailored to certain types of cargo and target cells by incorporation of PEG-containing lipoconjugates in the cationic liposome’s composition. Here, we report on the synthesis of novel PEG-containing lipoconjugates with molecular masses of PEG 800, 1500 and 2000 Da. PEG-containing lipoconjugates were used as one of the components in liposome preparation with the polycationic amphiphile 1,26-bis(cholest-5-en-3β-yloxycarbonylamino)-7,11,16,20-tetra-azahexacosan tetrahydrochloride (2X3) and the lipid-helper dioleoylphosphatidylethanolamine (DOPE). We demonstrate that increasing the length of the PEG chain reduces the transfection activity of liposomes in vitro, but improves the biodistribution, increases the circulation time in the bloodstream and enhances the interferon-inducing activity of immunostimulating RNA in vivo.
Time-Resolved Spectroscopic and Density Functional Theory Investigation of the Photogeneration of a Bifunctional Quinone Methide in Neutral and Basic Aqueous Solutions
Authors: Yan Zhiping , Du Lili , Lan Xin , Li Yuanchun , Wang Wenchao , Phillips David Lee
Published: November 2018

Binol quinone methides (BQMs) can be generated from 1,1′-(2,2′-dihydroxy-1,1′-binaphthyl-6,6′-diyl)bis(N,N,N-trimethylmethanamiuium) bromide (BQMP-b) in a 1:1 MeCN:H2O mixed solution via a ground state intramolecular proton transfer (GSIPT), as mentioned in our previously reported studies. Here, the photoreaction of BQMP-b in neutral and basic aqueous solution (pH = 7, 10, 12) was investigated to explore the possible mechanisms and the key intermediates produced in the process of the photoreaction and to examine whether they are different from those in a neutral mild-mixed MeCN:H2O solution. The studies were conducted using femtosecond transient absorption (fs-TA), nanosecond transient absorption (ns-TA), and nanosecond time-resolved resonance Raman spectroscopy (ns-TR3) in conjunction with results from density functional theory (DFT) computations. The results showed that BQMP-b was deprotonated initially and produced BQMs species more effectively through an E1bc elimination reaction in a strong basic aqueous condition (pH = 12), which differed from the reaction pathway that took place in the solution with pH = 7 or 10. A related single naphthol ring molecule 1-(6-hydroxynaphthalen-2-yl)-N,N,N-trimethylmethanaminium bromide (QMP-b) that did not contain a second naphthol ring was also investigated. The related reaction mechanisms are elucidated in this work, and it is briefly discussed how the mechanisms vary as a function of aqueous solution pH conditions.
Phytochemical Profile, Antioxidant and Antidiabetic Activities of Adansonia digitata L. (Baobab) from Mali, as a Source of Health-Promoting Compounds
Authors: Braca Alessandra , Sinisgalli Chiara , De Leo Marinella , Muscatello Beatrice , Cioni Pier Luigi , Milella Luigi , Ostuni Angela , Giani Sergio , Sanogo Rokia
Published: November 2018

Background: Adansonia digitata L. (Malvaceae), also known as baobab, is a tree attracting recent interest especially due to the high nutritional value of the fruit pulp. However, few studies are reported on the secondary metabolite content, showing high variability depending on the geographic region. Methods: In this study, the chemical profiles of Malian commercial baobab fruits and leaves, focused on phenolic content, were investigated by HPLC coupled with a photodiode array (PDA)/UV and an electrospray ionization (ESI) mass spectrometer (MS) and gas chromatography (GC)/MS. In addition, the extracts of fruit pulps obtained from three different markets (Fruits 1, 2, and 3) were evaluated for their total phenolic content (TPC), antioxidant activity and α-glucosidase inhibition. Results: Baobab fruit pulps were found to be rich in procyanidins and flavonol glycosides, with tiliroside as the major constituent. The baobab leaves showed a similar profile respect to the fruits, but with more detected phenolics. All fruit pulp extracts exerted antioxidant activity (highest for Fruit 3) and higher α-glucosidase inhibition than acarbose used as standard. Conclusions: This study confirmed the variability of baobab with different origins and indicated Malian species baobab as a promising source of health-promoting substances.
Low Power Consumption Red Light-Emitting Diodes Based on Inorganic Perovskite Quantum Dots under an Alternating Current Driving Mode
Authors: Liu Jingjing , Lu Zhangbo , Zhang Xianju , Zhang Yangyi , Ma Haiguang , Ji Yang , Xu Xiangxing , Yu Linwei , Xu Jun , Chen Kunji
Published: November 2018

Inorganic perovskites have emerged as a promising candidate for light-emitting devices due to their high stability and tunable band gap. However, the power consumption and brightness have always been an issue for perovskite light-emitting diodes (PeLEDs). Here, we improved the luminescence intensity and decreased the current density of the PeLEDs based on CsPbI3 quantum dots (QDs) and p-type Si substrate through an alternating current (AC) driving mode. For the different driving voltage modes (under a sine pulsed bias or square pulsed bias), a frequency-dependent electroluminescent (EL) behavior was observed. The devices under a square pulsed bias present a stronger EL intensity under the same voltage due to less thermal degradation at the interface. The red PeLEDs under a square pulsed bias driving demonstrate that the EL intensity drop-off phenomenon was further improved, and the integrated EL intensity shows the almost linear increase with the increasing driving voltage above 8.5 V. Additionally, compared to the direct current (DC) driving mode, the red PeLEDs under the AC condition exhibit higher operating stability, which is mainly due to the reducing accumulated charges in the devices. Our work provides an effective approach for obtaining strong brightness, low power consumption, and high stability light-emitting devices, which will exert a profound influence on coupling LEDs with household power supplies directly.
Serum Levels of miR-148a and miR-21-5p Are Increased in Type 1 Diabetic Patients and Correlated with Markers of Bone Strength and Metabolism
Authors: Grieco Giuseppina E. , Cataldo Dorica , Ceccarelli Elena , Nigi Laura , Catalano Giovanna , Brusco Noemi , Mancarella Francesca , Ventriglia Giuliana , Fondelli Cecilia , Guarino Elisa , Crisci Isabella , Sebastiani Guido , Dotta Francesco
Published: November 2018

Type 1 diabetes (T1D) is characterized by bone loss and altered bone remodeling, resulting into reduction of bone mineral density (BMD) and increased risk of fractures. Identification of specific biomarkers and/or causative factors of diabetic bone fragility is of fundamental importance for an early detection of such alterations and to envisage appropriate therapeutic interventions. MicroRNAs (miRNAs) are small non-coding RNAs which negatively regulate genes expression. Of note, miRNAs can be secreted in biological fluids through their association with different cellular components and, in such context, they may represent both candidate biomarkers and/or mediators of bone metabolism alterations. Here, we aimed at identifying miRNAs differentially expressed in serum of T1D patients and potentially involved in bone loss in type 1 diabetes. We selected six miRNAs previously associated with T1D and bone metabolism: miR-21; miR-24; miR-27a; miR-148a; miR-214; and miR-375. Selected miRNAs were analyzed in sera of 15 T1D patients (age: 33.57 ± 8.17; BMI: 21.4 ± 1.65) and 14 non-diabetic subjects (age: 31.7 ± 8.2; BMI: 24.6 ± 4.34). Calcium, osteocalcin, parathormone (PTH), bone ALkaline Phoshatase (bALP), and Vitamin D (VitD) as well as main parameters of bone health were measured in each patient. We observed an increased expression of miR-148a (p = 0.012) and miR-21-5p (p = 0.034) in sera of T1D patients vs. non-diabetic subjects. The correlation analysis between miRNAs expression and the main parameters of bone metabolism, showed a correlation between miR-148a and Bone Mineral Density (BMD) total body (TB) values (p = 0.042) and PTH circulating levels (p = 0.033) and the association of miR-21-5p to Bone Mineral Content-Femur (BMC-FEM). Finally, miR-148a and miR-21-5p target genes prediction analysis revealed several factors involved in bone development and remodeling, such as MAFB, WNT1, TGFB2, STAT3, or PDCD4, and the co-modulation of common pathways involved in bone homeostasis thus potentially assigning a role to both miR-148a and miR-21-5p in bone metabolism alterations. In conclusion, these results lead us to hypothesize a potential role for miR-148a and miR-21-5p in bone remodeling, thus representing potential biomarkers of bone fragility in T1D.
Impact of Chirp in High-Capacity Optical Metro Networks Employing Directly-Modulated VCSELs
Authors: Rapisarda Mariangela , Gatto Alberto , Martelli Paolo , Parolari Paola , Neumeyr Christian , Svaluto Moreolo Michela , Fabrega Josep M. , Nadal Laia , Boffi Pierpaolo
Published: November 2018

Directly modulated long-wavelength vertical cavity surface emitting lasers (VCSELs) are considered for the implementation of sliceable bandwidth/bitrate variable transceivers for very high capacity transmission (higher than 50 Gb/s per wavelength) in metropolitan area systems characterized by reduced cost, power consumption, and footprint. The impact of the frequency chirp measured for InP VCSELs with different kinds of design (high-bandwidth very short cavity and widely-tunable with micro electro-mechanical systems (MEMS) top mirror) is analyzed in case of discrete multitone (DMT) direct modulation in combination with 25-GHz wavelength selective switch (WSS) filtering. The maximum transmitted capacity for both dual side- and single side-band DMT modulation is evaluated as a function of the number of crossed nodes in a mesh metro network, comparing VCSEL based transmitters performance also with the case of external electro-absorption modulator use. Finally, the maximum reach achieved based on the received optical signal to noise ratio (OSNR) and the fiber span length is discussed. The results confirm the possibility to use directly-modulated long-wavelength VCSELs for the realization of sliceable bandwidth/bitrate variable transmitters targeting 50-Gb/s capacity per polarization, also in the presence of 5 crossed WSSs for reaches of hundreds of kilometers in multi-span Erbium-doped fiber amplified (EDFA) metro links supported by coherent detection.
Absolute and Precise Terahertz-Wave Radar Based on an Amplitude-Modulated Resonant-Tunneling-Diode Oscillator
Authors: Dobroiu Adrian , Wakasugi Ryotaka , Shirakawa Yusuke , Suzuki Safumi , Asada Masahiro
Published: November 2018

We present the principle of a terahertz-wave radar and its proof-of-concept experimental verification. The radar is based on a 522 GHz resonant-tunneling-diode oscillator, whose terahertz output power can be easily modulated by superimposing the modulation signal on its bias voltage. By using one modulation frequency and measuring the time delay of the returning signal, a relative measurement of the propagation distance is possible; adding a second modulation frequency removes the ambiguity stemming from the periodicity of the modulation sine wave and allows an absolute distance measurement. We verified this measurement method experimentally and obtained a submillimeter precision, as predicted by theory.
Electrospun Enzymatic Hydrolysis Lignin-Based Carbon Nanofibers as Binder-Free Supercapacitor Electrodes with High Performance
Authors: Wang Xiang , Zhang Wei , Chen Minzhi , Zhou Xiaoyan
Published: November 2018

Carbon nanofibers consisting of Poly(acrylonitrile) (PAN) and enzymatic hydrolysis lignin (EHL) were prepared in the present study by electrospinning followed by stabilization in air and carbonization in N2 environment. The morphology and structure of the electrospun carbon nanofibers were characterized by Scanning Electron Microscopy (SEM), Brunauer-Emmett-Teller (BET), Roman, and the electrochemical performances were then evaluated by cyclic voltammetry (CV), galvanostatic charge-discharge (GCD), and electrochemical impedance spectroscopy (EIS)methods. When the amount of EHL was 60 wt. %, the as-prepared nanofibers have the smallest average diameter of 172 nm and the largest BET specific surface area of 675 m2/g without activating treatment. The carbon nanofiber electrode showed excellent specific capacitance of 216.8 F/g at the current density of 1 A/g, maintaining 88.8% capacitance retention after 2000 cycles. Moreover, the carbon nanofiber electrode containing 60 wt. % exhibited a smaller time constant (0.5 s) in comparison to that of carbon nanofibers in literatures. These findings suggest the potential use of EHL could be a practical as a sustainable alternative for PAN in carbon electrode manufacturing.
Tuning Carbon Dots’ Optoelectronic Properties with Polymers
Authors: Dimos Konstantinos
Published: November 2018

Due to their unique properties of photoluminescence, biocompatibility, photostability, ease of preparing, and low cost, carbon dots have been studied extensively over the last decade. Soon after their discovery, it was realized that their main optical attributes may be protected, enhanced, and tuned upon proper surface passivation or functionalization. Therefore, up to date, numerous polymers have been used for these purposes, resulting to higher-quality carbon dots regarding their quantum yield or further emission-related aspects and compared to the primitive, bare ones. Hence, this review aims to clarify the polymers’ role and effect on carbon dots and their features focusing on the quality characteristics of their photoluminescence upon passivation or functionalization. Given in fact the numbers of relevant publications, emphasis is given on recent articles capturing the latest advances for polymers in carbon dots for expanding emission lifetimes, advancing quantum yields, tuning emission wavelengths, enhancing specific spectral range absorption, and tailoring optoelectronic properties in general.
An Efficient Solitary Senior Citizens Care Algorithm and Application: Considering Emotional Care for Big Data Collection
Authors: Huh Jun-Ho
Published: November 2018

The issue of solitary senior citizens dying alone has become serious in advanced countries where the average lifespan of their citizens is continuously extending due to improved health care and diet. Such unattended deaths are considered to be one of the major issues pertaining to the ever-growing number of senior citizens so that many research studies have been conducted to find a solution to mitigate the situation. The framework proposed in this study allows monitoring of electric power consumption patterns of solitary senior citizens. At the same time, a test bed was constructed to estimate the performance of the framework. The results from the test bed experiment revealed that the framework was effective, flexible, and expandable for actual implementation. This framework is the product of these research studies describing individual designs and the method of implementing them for actual application. This research has confirmed that the framework for an extendable solitary senior citizens care system can be designed and implemented at low cost and the operations between system components worked smoothly while interacting flexibly. In particular, the rate of these old people dying alone in poor areas was above normal so that the proposed system would be quite meaningful to society as it helps in monitoring their safety by locating the whereabouts of those people with dementia or checking their daily routines, for example.
MISR-GOES 3D Winds: Implications for Future LEO-GEO and LEO-LEO Winds
Authors: L. Carr James , L. Wu Dong , A. Kelly Michael , Gong Jie
Published: November 2018

Global wind observations are fundamental for studying weather and climate dynamics and for operational forecasting. Most wind measurements come from atmospheric motion vectors (AMVs) by tracking the displacement of cloud or water vapor features. These AMVs generally rely on thermal infrared (IR) techniques for their height assignments, which are subject to large uncertainties in the presence of weak or reversed vertical temperature gradients near the planetary boundary layer (PBL) and tropopause folds. Stereo imaging can overcome the height assignment problem using geometric parallax for feature height determination. In this study we develop a stereo 3D-Wind algorithm to simultaneously retrieve AMV and height from geostationary (GEO) and low Earth orbit (LEO) satellite imagery and apply it to collocated Geostationary Operational Environmental Satellite (GOES) and Multi-angle Imaging SpectroRadiometer (MISR) imagery. The new algorithm improves AMV and height relative to products from GOES or MISR alone, with an estimated accuracy of <0.5 m/s in AMV and <200 m in height with 2.2 km sampling. The algorithm can be generalized to other LEO-GEO or LEO-LEO combinations for greater spatiotemporal coverage. The technique demonstrated with MISR and GOES has important implications for future high-quality AMV observations, for which a low-cost constellation of CubeSats can play a vital role.
Opium Poppy Detection Using Deep Learning
Authors: Liu Xiangyu , Tian Yichen , Yuan Chao , Zhang Feifei , Yang Guang
Published: November 2018

Opium poppies are a major source of traditional drugs, which are not only harmful to physical and mental health, but also threaten the economy and society. Monitoring poppy cultivation in key regions through remote sensing is therefore a crucial task; the location coordinates of poppy parcels represent particularly important information for their eradication by local governments. We propose a new methodology based on deep learning target detection to identify the location of poppy parcels and map their spatial distribution. We first make six training datasets with different band combinations and slide window sizes using two ZiYuan3 (ZY3) remote sensing images and separately train the single shot multibox detector (SSD) model. Then, we choose the best model and test its performance using 225 km2 verification images from Lao People’s Democratic Republic (Lao PDR), which exhibits a precision of 95% for a recall of 85%. The speed of our method is 4.5 km2/s on 1080TI Graphics Processing Unit (GPU). This study is the first attempt to monitor opium poppies with the deep learning method and achieve a high recognition rate. Our method does not require manual feature extraction and provides an alternative way to rapidly obtain the exact location coordinates of opium poppy cultivation patches.
Farmer Perception, Recollection, and Remote Sensing in Weather Index Insurance: An Ethiopia Case Study
Authors: Osgood Daniel , Powell Bristol , Diro Rahel , Farah Carlos , Enenkel Markus , Brown Molly E. , Husak Greg , Blakeley S. Lucille , Hoffman Laura , McCarty Jessica L.
Published: November 2018

A challenge in addressing climate risk in developing countries is that many regions have extremely limited formal data sets, so for these regions, people must rely on technologies like remote sensing for solutions. However, this means the necessary formal weather data to design and validate remote sensing solutions do not exist. Therefore, many projects use farmers’ reported perceptions and recollections of climate risk events, such as drought. However, if these are used to design risk management interventions such as insurance, there may be biases and limitations which could potentially lead to a problematic product. To better understand the value and validity of farmer perceptions, this paper explores two related questions: (1) Is there evidence that farmers reporting data have any information about actual drought events, and (2) is there evidence that it is valuable to address recollection and perception issues when using farmer-reported data? We investigated these questions by analyzing index insurance, in which remote sensing products trigger payments to farmers during loss years. Our case study is perhaps the largest participatory farmer remote sensing insurance project in Ethiopia. We tested the cross-consistency of farmer-reported seasonal vulnerabilities against the years reported as droughts by independent satellite data sources. We found evidence that farmer-reported events are independently reflected in multiple remote sensing datasets, suggesting that there is legitimate information in farmer reporting. Repeated community-based meetings over time and aggregating independent village reports over space lead to improved predictions, suggesting that it may be important to utilize methods to address potential biases.
Fully Connected Conditional Random Fields for High-Resolution Remote Sensing Land Use/Land Cover Classification with Convolutional Neural Networks
Authors: Zhang Bin , Wang Cunpeng , Shen Yonglin , Liu Yueyan
Published: November 2018

The interpretation of land use and land cover (LULC) is an important issue in the fields of high-resolution remote sensing (RS) image processing and land resource management. Fully training a new or existing convolutional neural network (CNN) architecture for LULC classification requires a large amount of remote sensing images. Thus, fine-tuning a pre-trained CNN for LULC detection is required. To improve the classification accuracy for high resolution remote sensing images, it is necessary to use another feature descriptor and to adopt a classifier for post-processing. A fully connected conditional random fields (FC-CRF), to use the fine-tuned CNN layers, spectral features, and fully connected pairwise potentials, is proposed for image classification of high-resolution remote sensing images. First, an existing CNN model is adopted, and the parameters of CNN are fine-tuned by training datasets. Then, the probabilities of image pixels belong to each class type are calculated. Second, we consider the spectral features and digital surface model (DSM) and combined with a support vector machine (SVM) classifier, the probabilities belong to each LULC class type are determined. Combined with the probabilities achieved by the fine-tuned CNN, new feature descriptors are built. Finally, FC-CRF are introduced to produce the classification results, whereas the unary potentials are achieved by the new feature descriptors and SVM classifier, and the pairwise potentials are achieved by the three-band RS imagery and DSM. Experimental results show that the proposed classification scheme achieves good performance when the total accuracy is about 85%.
Super-Resolution Multi-Look Detection in SAR Tomography
Authors: Dănișor Cosmin , Fornaro Gianfranco , Pauciullo Antonio , Reale Diego , Datcu Mihai
Published: November 2018

Synthetic Aperture Radar (SAR) Tomography (TomoSAR) allows extending the 2-D focusing capabilities of SAR to the elevation direction, orthogonal to the azimuth and range. The multi-dimensional extension (along the time) also enables the monitoring of possible scatterer displacements. A key aspect of TomoSAR is the identification, in the presence of noise, of multiple persistent scatterers interfering within the same 2-D (azimuth range plane) pixel. To this aim, the use of multi-look has been shown to provide tangible improvements in the detection of single and double interfering persistent scatterers at the expense of a minor spatial resolution loss. Depending on the system acquisition characteristics, this operation may require also the detection of multiple scatterers interfering at distances lower than the Rayleigh resolution (super-resolution). In this work we further investigated the use of multi-look in TomoSAR for the detection of multiple scatterers located also below the Rayleigh resolution. A solution relying on the Capon filtering was first analyzed, due to its improved capabilities in the separation of the responses of multiple scatterers and sidelobe suppression. Moreover, in the framework of the Generalized Likelihood Ratio Test (GLRT), the single-look support based detection strategy recently proposed in the literature was extended to the multi-look case. Experimental results of tests carried out on two datasets acquired by TerraSAR-X and COSMO-SkyMED sensors are provided to show the performances of the proposed solution as well as the effects of the baseline span of the dataset for the detection capabilities of interfering scatterers.
Automated Open Cotton Boll Detection for Yield Estimation Using Unmanned Aircraft Vehicle (UAV) Data
Authors: Yeom Junho , Jung Jinha , Chang Anjin , Maeda Murilo , Landivar Juan
Published: November 2018

Unmanned aerial vehicle (UAV) images have great potential for various agricultural applications. In particular, UAV systems facilitate timely and precise data collection in agriculture fields at high spatial and temporal resolutions. In this study, we propose an automatic open cotton boll detection algorithm using ultra-fine spatial resolution UAV images. Seed points for a region growing algorithm were generated hierarchically with a random base for computation efficiency. Cotton boll candidates were determined based on the spatial features of each region growing segment. Spectral threshold values that automatically separate cotton bolls from other non-target objects were derived based on input images for adaptive application. Finally, a binary cotton boll classification was performed using the derived threshold values and other morphological filters to reduce noise from the results. The open cotton boll classification results were validated using reference data and the results showed an accuracy higher than 88% in various evaluation measures. Moreover, the UAV-extracted cotton boll area and actual crop yield had a strong positive correlation (0.8). The proposed method leverages UAV characteristics such as high spatial resolution and accessibility by applying automatic and unsupervised procedures using images from a single date. Additionally, this study verified the extraction of target regions of interest from UAV images for direct yield estimation. Cotton yield estimation models had R2 values between 0.63 and 0.65 and RMSE values between 0.47 kg and 0.66 kg per plot grid.
Self-Sensing CFRP Fabric for Structural Strengthening and Damage Detection of Reinforced Concrete Structures
Authors: Feng Qian , Ou Jinping
Published: November 2018

This paper presents a concept of a Self-sensing Carbon Fiber Reinforced Polymer (SCFRP) system, which integrates the piezoceramic transducers with the common concrete strengthening materials, CFRP fabric. This integration provides the SCFRP fabric with the ability to monitor the structural health condition when the SCFRP fabric is applied on reinforced concrete structures. In order to validate the feasibility of this system, several three-point bending beam (3PBB) specimens were fabricated and tested before and after the specimens were reinforced with the proposed SCFRP fabric. In addition, the specimens with the low (C25) and high (C40) concrete grades were also experimentally investigated to evaluate the reinforced effectiveness of the SCFRP fabric. Finally, the experimental results demonstrate that the proposed SCFRP fabric can significantly improve the bearing capacity of the concrete structures, and provided the reinforced concrete structures with an ability of self-sensing their health condition.
A Fast ML-Based Single-Step Localization Method Using EM Algorithm Based on Time Delay and Doppler Shift for a Far-Field Scenario
Authors: Qin Tianzhu , Li Lin , Ba Bin , Wang Daming
Published: November 2018

This study discusses the localization problem based on time delay and Doppler shift for a far-field scenario. The conventional location methods employ two steps that first extract intermediate parameters from the received signals and then determine the source position from the measured parameters. As opposed to the traditional two-step methods, the direct position determination (DPD) methods accomplish the localization in a single step without computing intermediate parameters. However, the DPD cost function often remains non-convex, thereby it will cost a high amount of computational resources to find the estimated position through traversal search. Weiss proposed a DPD estimator to mitigate the computational complexity via eigenvalue decomposition. Unfortunately, when the computational resources are rather limited, Weiss’s method fails to satisfy the timeliness. To solve this problem, this paper develops a DPD estimator using expectation maximization (EM) algorithm based on time delay and Doppler shift. The proposed method starts from choosing the transmitter-receiver range vector as the hidden variable. Then, the cost function is separated and simplified via the hidden variable, accomplishing the transformation from the high dimensional nonlinear search problem into a few one dimensional search subproblems. Finally, the expressions of EM repetition are obtained through Laplace approximation. In addition, we derive the Cramér–Rao bound to evaluate the best localization performance in this paper. Simulation results confirm that, on the basis of guaranteeing high accuracy, the proposed algorithm makes a good compromise in localization performance and computational complexity.
Antiresonant Reflecting Guidance and Mach-Zender Interference in Cascaded Hollow-Core Fibers for Multi-Parameter Sensing
Authors: Hou Maoxiang , He Jun , Xu Xizhen , Li Ziliang , Zhang Zhe , Guo Kuikui , Ju Shuai , Wang Yiping
Published: November 2018

We propose and demonstrate a cascaded hollow-core fiber (HCF) device for multi-parameter sensing based on the combination of antiresonant reflecting guidance (ARRG) and Mach-Zender interference (MZI). The device was fabricated by splicing two sections of HCF together. Two sets of fringes, which have different free spectral ranges, were generated from ARRG and MZI, respectively, and were aliasing in the transmission spectrum. The two sets of fringes were then separated using a band pass filter and a Gaussian fitting technique. The wavelengths at two transmission loss dips formed by ARRG and MZI exhibit a temperature sensitivity of 14.1 and 28.5 pm/°C, and a strain sensitivity of 0.4 and −0.8 pm/με, respectively. By using a crossing matrix with differences sensitivities, the cross-sensitivity between temperature and strain can be solved. The gas pressure response of the cascaded HCF device was also tested up to 300 °C, and linear relationships between the gas pressure sensitivities and temperature were found, which can be used in gas pressure application in various temperatures. Moreover, the proposed cascaded HCF sensor is compact, low cost, and simple for fabrication, and hence offers a promising way for the simultaneous measurement of multiple parameters, such as temperature, strain, and gas pressure.
Indoor Positioning Based on Pedestrian Dead Reckoning and Magnetic Field Matching for Smartphones
Authors: Kuang Jian , Niu Xiaoji , Zhang Peng , Chen Xingeng
Published: November 2018

This paper presents an ambient magnetic field map-based matching (MM) positioning algorithm for smartphones in an indoor environment. To improve the low distinguishability of a magnetic field fingerprint at a single point, a magnetic field sequence (MFS) combined with the measured trajectory contour coming from pedestrian dead-reckoning (PDR) is used for MM. Based on the fast approximation of magnetic field gradient, a Gauss-Newton iterative (GNI) method is used to find a rigid transformation that optimally aligns the measured MFS with a reference MFS coming from the magnetic field map. Then, the position of the reference MFS is used to control the position drift error of the inertial navigation system (INS) based PDR by an extended Kalman filter (EKF) and to further improve the accuracy of the trajectory contour. Finally, we conduct several experiments to evaluate the navigation performance of the proposed MM algorithm. The test results show that the position estimation error of the MM algorithm is 0.64 m (RMS) in an office building environment, 1.87 m (RMS) in a typical lobby environment, and 2.34 m (RMS) in a shopping mall environment.
Indoor Pedestrian Self-Positioning Based on Image Acoustic Source Impulse Using a Sensor-Rich Smartphone
Authors: Song Xiyu , Wang Mei , Qiu Hongbing , Luo Liyan
Published: November 2018

The ubiquity of sensor-rich smartphones provides opportunities for a low-cost method to track indoor pedestrians. In this situation, pedestrian dead reckoning (PDR) is a widely used technology; however, its cumulative error seriously affects its accuracy. This paper presents a method of combining infrastructure-free indoor acoustic self-positioning with PDR self-positioning, which verifies the rationality of PDR results through the acoustic constraint between a sound source and its image sources. We further determine the first-order echo delay measurements, thus obtaining the mobile user position. We verify that the proposed method can achieve a continuous self-positioning median error of 0.19 m, and the error probability below 0.12 m is 54.46%, which indicates its ability to eliminate PDR error, as well as its adaptability to environmental disturbances.
Study on Residual Vibration Suppress of a 3-DOF Flexible Parallel Robot Mechanism
Authors: Zhang Qinghua , Lu Qinghua , Zhang Xianmin , Wu Junjun
Published: November 2018

Residual vibration suppression of a 3-DOF flexible parallel robot mechanism is implemented in this paper. Considering the direct and inverse piezoelectric effect of PZT (lead zirconium titanate) material, a general motion equation is established which includes an input equation of PZT actuators and an output equation of PZT sensors. A strain and strain rate feedback (SSRF) controller is designed based on the established general motion equation. A numerical simulation is implemented to verify the effectiveness of the SSRF controller in driving the proposed robotic mechanism. The simulation results reveal that the SSRF controller can decrease the elastic vibration displacement of the flexible links rapidly and improve the position accuracy of the moving platform. In the experimental study, one scheme with three passive flexible links is controlled by the SSRF controller at the same time as the performance of the introduced solutions. The experimental results show that the strain and strain rate feedback controller is able to effectively suppress the residual vibration of the 3-DOF flexible parallel robot mechanism. The results of the numerical simulation and experiment are completely consistent.
Detection and Validation of Tow-Away Road Sign Licenses through Deep Learning Methods
Authors: Balducci Fabrizio , Impedovo Donato , Pirlo Giuseppe
Published: November 2018

This work presents the practical design of a system that faces the problem of identification and validation of private no-parking road signs. This issue is very important for the public city administrations since many people, after receiving a code that identifies the signal at the entrance of their private car garage as valid, forget to renew the code validity through the payment of a city tax, causing large money shortages to the public administration. The goal of the system is twice since, after recognition of the official road sign pattern, its validity must be controlled by extracting the code put in a specific sub-region inside it. Despite a lot of work on the road signs’ topic having been carried out, a complete benchmark dataset also considering the particular setting of the Italian law is today not available for comparison, thus the second goal of this work is to provide experimental results that exploit machine learning and deep learning techniques that can be satisfactorily used in industrial applications.
Development of Marker-Free Night-Vision Displacement Sensor System by Using Image Convex Hull Optimization
Authors: Choi Insub , Kim JunHee , Jang Jisang
Published: November 2018

Vision-based displacement sensors (VDSs) have the potential to be widely used in the structural health monitoring field, because the VDSs are generally easier to install and have higher applicability to the existing structures compared to the other conventional displacement sensors. However, the VDS also has disadvantages, in that ancillary markers are needed for extracting displacement data and data reliability is significantly lowered at night. In this study, a night vision displacement sensor (NVDS) was proposed to overcome the aforementioned two limitations. First, a non-contact NVDS system is developed with the installation of the infrared (IR) pass filter. Since it utilizes the wavelength of the infrared region and it is not sensitive to the change of a visible ray, it can precisely extract the shape information of the structure even at night. Second, a technique to extract the feature points from the images without any ancillary marker was formulated through an image convex hull optimization. Finally, the experimental tests of a three-story scaled model were performed to investigate the effectiveness of proposed NVDS at night. The results demonstrate that the NVDS has sufficiently high accuracy even at night and it can precisely measure the dynamic characteristics such as mode shapes and natural frequencies of the structure. The proposed system and formulation would extend the applicability of vision sensor not only into night-time measure but also marker-free measure.
Cooperative UAV Scheme for Enhancing Video Transmission and Global Network Energy Efficiency
Authors: Cumino Pedro , Lobato Junior Wellington , Tavares Thais , Santos Hugo , Rosário Denis , Cerqueira Eduardo , Villas Leandro , Gerla Mario
Published: November 2018

Collaboration between multiple Unmanned Aerial Vehicles (UAVs) to set up a Flying Ad Hoc Network (FANET) is a growing trend since future applications claim for more autonomous and rapid deployable systems. The user experience on watching videos transmitted over FANETs should always be satisfactory even under influence of topology changes caused by the energy consumption of UAVs. In addition, the FANET must keep the UAVs cooperating as much as possible during a mission. However, one of the main challenges in FANET is how to mitigate the impact of limited energy resources of UAVs on the FANET operation in order to monitor the environment for a long period of time. In this sense, UAV replacement is required in order to avoid the premature death of nodes, network disconnections, route failures, void areas, and low-quality video transmissions. In addition, decision-making must take into account energy consumption associated with UAV movements, since they are generally quite energy-intensive. This article proposes a cooperative UAV scheme for enhancing video transmission and global energy efficiency called VOEI. The main goal of VOEI is to maintain the video with QoE support while supporting the nodes with a good connectivity quality level and flying for a long period of time. Based on an Software Defined Network (SDN) paradigm, the VOEI assumes the existence of a centrailized controller node to compute reliable and energy-efficiency routes, as well as detects the appropriate moment for UAV replacement by considering global FANET context information to provide energy-efficiency operations. Based on simulation results, we conclude that VOEI can effectively mitigate the energy challenges of FANET, since it provides energy-efficiency operations, avoiding network death, route failure, and void area, as well as network partitioning compared to state-of-the-art algorithm. In addition, VOEI delivers videos with suitable Quality of Experience (QoE) to end-users at any time, which is not achieved by the state-of-the-art algorithm.
Applicability of Diffuse Ultrasound to Evaluation of the Water Permeability and Chloride Ion Penetrability of Cracked Concrete
Authors: Ahn Eunjong , Gwon Seongwoo , Kim Hyunjun , Kim Chanyoung , Sim Sung-Han , Shin Myoungsu
Published: November 2018

This study aims to explore the applicability of diffuse ultrasound to the evaluation of water permeability and chloride ion penetrability of cracked concrete. Lab-scale experiments were conducted on disk-shaped concrete specimens, each having a different width of a penetrating crack that was generated by splitting tension along the centerline. The average crack width of each specimen was determined using an image binarization technique. The diffuse ultrasound test employed signals in the frequency range of 200 to 440 kHz. The water flow rate was measured using a constant water-head permeability method, and the chloride diffusion coefficient was determined using a modified steady-state migration method. Then, the effects of crack width on the diffusion characteristics of ultrasound (i.e., diffusivity, dissipation), water flow rate, and chloride diffusion coefficient are investigated. The correlations between the water flow rate and diffuse ultrasound parameters, and between the chloride diffusion coefficient and diffuse ultrasound parameters, are examined. The results suggest that diffuse ultrasound is a promising method for assessing the water permeability and chloride ion penetrability of cracked concrete.
A Fast Calibration and Compensation Method for Magnetometers in Strap-Down Spinning Projectiles
Authors: Long Dafeng , Zhang Xiaoming , Wei Xiaohui , Luo Zhongliang , Cao Jianzhong
Published: November 2018

Attitude measurement is an essential technology in projectile trajectory correction. Magnetometers have been used for projectile attitude measurement systems as they are small in size, lightweight, and low cost. However, magnetometers are seriously disturbed by the artillery magnetic field during launch. Moreover, the error parameters of the magnetometers, which are calibrated in advance, usually change after extended storage. The changed parameters have negative effects on attitude estimation of the projectile. To improve the accuracy of attitude estimation, the magnetometers should be calibrated again before launch or during flight. This paper presents a fast calibration method specific for a spinning projectile. At the launch site, the tri-axial magnetometer is calibrated, the parameters of magnetometer are quickly obtained by optimal ellipsoid fitting based on a least squares criterion. Then, the calibration parameters are used to compensate for magnetometer outputs during flight. The numerical simulation results show that the proposed calibration method can effectively determine zero bias, scale factors, and alignment angle errors. Finally, a semi-physical experimental system was designed to further verify the performance of the calibration method. The results show that pitch angle error reduces from 3.52° to 0.58° after calibration. The roll angle error is reduced from 2.59° to 0.65°. Simulations and experimental results indicate that the accuracy of magnetometer in strap-down spinning projectile has been greatly enhanced, and the attitude estimation errors are reduced after calibration.
Robust Drivable Road Region Detection for Fixed-Route Autonomous Vehicles Using Map-Fusion Images
Authors: Cai Yichao , Li Dachuan , Zhou Xiao , Mou Xingang
Published: November 2018

Environment perception is one of the major issues in autonomous driving systems. In particular, effective and robust drivable road region detection still remains a challenge to be addressed for autonomous vehicles in multi-lane roads, intersections and unstructured road environments. In this paper, a computer vision and neural networks-based drivable road region detection approach is proposed for fixed-route autonomous vehicles (e.g., shuttles, buses and other vehicles operating on fixed routes), using a vehicle-mounted camera, route map and real-time vehicle location. The key idea of the proposed approach is to fuse an image with its corresponding local route map to obtain the map-fusion image (MFI) where the information of the image and route map act as complementary to each other. The information of the image can be utilized in road regions with rich features, while local route map acts as critical heuristics that enable robust drivable road region detection in areas without clear lane marking or borders. A neural network model constructed upon the Convolutional Neural Networks (CNNs), namely FCN-VGG16, is utilized to extract the drivable road region from the fused MFI. The proposed approach is validated using real-world driving scenario videos captured by an industrial camera mounted on a testing vehicle. Experiments demonstrate that the proposed approach outperforms the conventional approach which uses non-fused images in terms of detection accuracy and robustness, and it achieves desirable robustness against undesirable illumination conditions and pavement appearance, as well as projection and map-fusion errors.
High Resolution and Fast Processing of Spectral Reconstruction in Fourier Transform Imaging Spectroscopy
Authors: Zhang Weikang , Wen Desheng , Song Zongxi , Wei Xin , Liu Gang , Li Zhixin
Published: November 2018

High-resolution spectrum estimation has continually attracted great attention in spectrum reconstruction based on Fourier transform imaging spectroscopy (FTIS). In this paper, a parallel solution for interference data processing using high-resolution spectrum estimation is proposed to reconstruct the spectrum in a fast high-resolution way. In batch processing, we use high-performance parallel-computing on the graphics processing unit (GPU) for higher efficiency and lower operation time. In addition, a parallel processing mechanism is designed for our parallel algorithm to obtain higher performance. At the same time, other solving algorithms for the modern spectrum estimation model are introduced for discussion and comparison. We compare traditional high-resolution solving algorithms running on the central processing unit (CPU) and the parallel algorithm on the GPU for processing the interferogram. The experimental results illustrate that runtime is reduced by about 70% using our parallel solution, and the GPU has a great advantage in processing large data and accelerating applications.
An Improved Inverse Beamforming Method: Azimuth Resolution Analysis for Weak Target Detection
Authors: Li Peng , Zhang Xinhua , Li Lanrui , Zhang Wenlong
Published: November 2018

The inverse beamforming (IBF) is a mature method to improve azimuth resolution. However, for weak targets it is not applicable as IBF enhances side lobes. In this paper, an improved IBF algorithm is proposed to raise the azimuth resolution under the premise of ensuring the detection ability for weak targets. Firstly, from the point of phase compensation, we analyze the cause of side lobes when IBF is applied. Then the improved IBF algorithm recorded as GIBF (the improved inverse beamforming) is proposed by changing the Toeplitz average into the phase construction. The theoretical derivation and simulation data processing show the proposed method can improve the resolution of the N sensors to the standard of 2N − 1 sensors under different signal-to-noise ratios. Compared with IBF, GIBF has great advantages in detecting weak targets. Passive sonar data are used to further verify the advantages of GIBF; the trajectories on azimuth history diagrams become clear, the azimuth resolution is improved, and the detection ability for weak targets is still robust. In addition, GIBF is combined with the common DOA (direction of arrival) estimation algorithms, such as conventional beamforming and minimum variance distortionless signal response, which proves the applicability of the algorithm.