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Tremendous historical and recent building vector maps are available from private surveying and mapping departments or open-source platforms such as Open Street Map (OSM). However, there invariably exist offsets between the building vectors and new remote sensing images, caused by geometric registration errors and parallax from hypsography. Consequently, these vector maps cannot be directly used as labels for the up-to-date GIS productions, as well as popular supervised machine learning. As the first work of this kind, this paper proposes an offset correction method, based on deep learning, to predict the bias between a vector building map and a new remote sensing image. The method is based on a dense regression model to predict the offsets between the image and the vector map at the pixel level, which are then processed to retrieve the offsets of each polygon. Two datasets consist of remote sensing images and biased building polygons, the WHU change detection and London datasets, are prepared to test the effectiveness of our approach. In the WHU change detection dataset, approaching 80% polygons can be correctly registered within the tolerance of three pixels, in the London dataset, more than 60% polygons can be corrected by a pre-trained model on an available open-source dataset, both of which demonstrated that our method can contribute to the GIS map updating and more efficient preparation of training samples for a deep learning model.

Exosome vesicles (EVs) released by macrophages are potential biomarkers for the analysis of immune responses. This study reports a high-throughput EV detection assay developed using a label-free EV microarray. The EV microarray consists of a panel of seven antibodies that are specific to multiple membrane receptors of the target EVs. The EV microarray was fabricated on a photonic crystal (PC) biosensor surface. The hyperspectral imaging approached was implemented to quantify the antibody and EV absorptions on the PC-based microarray. The label-free EV microarray enables low-cost, rapid, and high-throughput characterization of macrophage EVs with a significantly reduced sample volume of 1 μL.

This work reports a paper-based sensor technology for point-of-care nucleic acid amplification tests. The technology integrates a sensor chip and an Arduino-compatible fluorescence detector. The paper-based sensor provides the functions of reagent storage, sample transportation, and DNA amplification. The compact and low-cost fluorescence detector can quantify the amplicons in real time. The results show that the paper-based sensor can detect genomic DNA extracted from Escherichia coli with the concentration as low as 2 × 104 copies/ µL. As a diagnosis tool, the sensor has the potential to measure multiple target genes simultaneously.

This paper analyzes the magnetic lead screw (MLS) from the perspective of the airgap field harmonics for the accurate and fast parametric analysis and the performance test. According to the Maxwell stress tensor, formulas of calculating thrust force and torque can be given. Based on the method of the finite element analysis and the analytic calculation, the flux density distribution is analyzed. The impact of the "end effect" should be considered in the calculation of the thrust force of the MLS. The analytical results agree very well with the FEA results and the difference between the both is less than 1%. The torque and thrust force of the MLS are contributed by several dominating field harmonics. Quantitative comparisons are made for the parametric analysis of the MLS which assist to verify and complement existing conclusions.

This paper reports a novel nanofabrication approach that combines imprint and silver doping lithography (iSDL) to generate nanoscale patterns in chalcogenide (ChG) thin films. The iSDL approach is capable of controlling the photodoping of silver in amorphous ChG with a high spatial precision. The ChG nanophotonic devices with one-dimensional (1D) and two-dimensional (2D) periodic structures were fabricated and characterized.

The various ways of data collection for modern applications such as bioinformatics result in heterogeneous data, which presents challenges for traditional variable selection methods that assume data is independent and identically distributed. Existing statistical models accounting for unwanted variation can be applied for gene identification in heterogeneous genetic data, which however suffer from variable redundancy and also lack of predictability. To cope with that, we propose an embedded variable selection method for gene identification from a sparse learning perspective which is capable of accounting for unwanted heterogeneity blurring the true gene effects. Its performance is investigated by studying two different unsupervised and supervised gene identification problems in which the benchmark data samples are heterogeneous and collected with group structures. The results have demonstrated the superiority of our method over state-of-the art methods by effectively accounting for the unwanted heterogeneity in both cases.

Efforts in Europe for the deployment of Cooperative Intelligent Transport Systems (C-ITS) have seen a substantial increase in recent years, with various large-scale initiatives having been launched. For these systems two main communication methods are available: short-range ad-hoc local network direct vehicular (and infrastructure) communication based on the IEEE 802.11p standard, and communication via the cellular network. Substantial standardisation efforts have taken place for the first method, while cellular solutions for vehicular communication are still very fragmented. This paper presents a relevant features of an open, scalable and broker-centric architecture for connecting local systems using short-range communication to an infrastructure server, which uses an information broker. For the client side, a topic structure inside the broker facilitates an efficient method for geocasting. On top of this functionality, a combination of certification, web tokens and transport layer security is developed to ensure security. A link of the architecture to the relevant business models is made to demonstrate that the two are compatible.

This paper presents a multifunctional nanotransfer printing (nTP) method based on a simple stick-and-peel procedure that allows fast production of multiple optical nanodevices using Scotch tape. In addition to the capabilities of forming single- and multi-layer nanopatterned films on a tape, the present technique facilitates the transfer of nanostructures onto unconventional substrates (such as cleaved fiber facets and curved fiber sides) and fabrication of more complex optical devices, including Fabry-Perot cavities. Moreover, our stick-and-peel method can be applicable to various metallic and dielectric structures, including metamaterials with the feature size below 100 nm and TiO 2 nanopatterned films.

This paper reports on an efficient and convenient method of patterning nanostructures on the cleaved facet of an optical fiber. The fabrication method utilizes ultraviolet (UV) assisted nanoimprint lithography in which the fiber tip is pressed against a stamp carrying nanoscale patterns, and then is exposed to UV radiation. The novelty of this work lies in utilizing simpler fabrication steps with better control over angle of contact at the fiber tip, which leads to rapid formation of nanostructures with well-defined features. An array of nanoposts are patterned at fiber tip and coated with titanium oxide to work as a guided mode resonant (GMR) device. The sensitivity of the fiber-tip GMR device to surrounding refractive index is 183.3 nm per refractive index unit. The proposed nanofabrication method offers a promising approach to develop remote fiber-optic sensors with intrinsic optical beam alignment for detecting the presence of subtle concentration of analytes at the fiber tip.

A sol-gel based imprint lithography process has been developed to fabricate guided-mode resonance (GMR) structures. The inexpensive process offers a rapid means to create sub-micron grating waveguide structures over large surface areas. Both one-dimensional and two-dimensional GMR devices have been successfully fabricated and characterized.

Immunoassay based on laser-induced photoacoustic (PA) effect is demonstrated for the detection of disease biomarkers with a significantly enhanced sensitivity. The PA immunoassay employs metal nanoparticles as photoacoustically detectable labels. Compared to the colorimetric method, the PA approach offers sensitivity improvements over 60-fold and 100-fold for the microtiter plate-based immunoassay and the lateral flow immunoassay, respectively.

Resonance tuning characteristics of a plasmonic photonic crystal nanostructure under uniaxial compressive and tensile strains were investigated. The plasmonic device consists of a periodic array of metal-coated polymer nanoposts fabricated using a replica molding process.Applied strains regulate the period of the array, leading to flexible and repeatable resonance tuning of localized plasmons.

We investigate optical nanoantennas featuring asymmetrical stepped-junction structures. By breaking the symmetry of the conventional optical nanoantennas, the performance of them is improved in many aspects. Experiments have been conducted to validate the proposed design.

To build a driver steering model which can reflect drivers' lane-keeping characteristics, twelve drivers' naturalistic driving data on real inter-city highway are recorded. These data are used to analyze drivers' general characteristics in lane-keeping process and how factors, such as lane position, disturbing objects nearby and road curvature influence drivers' behaviors. Then, the concept of `expected lateral driving zone' and a driver steering behavior mechanism are proposed. A driver steering behavior model is designed based on this mechanism and predictive optimal control theory. Three typical scenarios are selected to compare this new model with a single-point preview model and driver's real steering behavior on performance. The results show that the new model can make a more accurate prediction about driver's steering angle.

The characteristics of low minor allele frequency (MAF) and weak individual effects make genome-wide association studies (GWAS) for rare variant single nucleotide polymorphisms (SNPs) more difficult when using conventional statistical methods. By aggregating the rare variant effects belonging to the same gene, collapsing is the most common way to enhance the detection of rare variant effects for association analyses with a given trait. In this paper, we propose a novel framework of MAF-based logistic principal component analysis (MLPCA) to derive aggregated statistics by explicitly modeling the correlation between rare variant SNP data, which is categorical. The derived aggregated statistics by MLPCA can then be tested as a surrogate variable in regression models to detect the gene-environment interaction from rare variants. In addition, MLPCA searches for the optimal linear combination from the best subset of rare variants according to MAF that has the maximum association with the given trait. We compared the power of our MLPCA-based methods with four existing collapsing methods in gene-environment interaction association analysis using both our simulation data set and Genetic Analysis Workshop 17 (GAW17) data. Our experimental results have demonstrated that MLPCA on two forms of genotype data representations achieves higher statistical power than those existing methods and can be further improved by introducing the appropriate sparsity penalty. The performance improvement by our MLPCA-based methods result from the derived aggregated statistics by explicitly modeling categorical SNP data and searching for the maximum associated subset of SNPs for collapsing, which helps better capture the combined effect from individual rare variants and the interaction with environmental factors.

We report for the first time the combination of a quartz-based photonic crystal (PC) with a detection instrument designed to perform label-free (LF) and enhanced fluorescence (EF) imaging for antibody microarray applications. Label-free detection is used to quantify binding density of immobilized capture antibodies. Angle-scanning approach is implemented to achieve more uniform fluorescence enhancement by reducing the coefficient of variation of replicate assays by 20–99% compared to ordinary fluorescence microscopy.

Professional Health Technicians are strategic resources of the development of health service, and the significant support of deepening the reform of pharmaceutical and healthcare systems in china. In view of the current situation of professional health technicians in Heilongjiang province, this paper first makes an analysis of major problems revealed in group of professional health technicians in Heilongjiang province, and then designs a Grey Dynamic Prediction Model according to Grey System Theory, and subsequently forecasts the demand of Heilongjiang professional health technicians from 2011 to 2020, and finally in accordance with forecasting results, proposes corresponding countermeasures for talents accumulation based on the notion of talent development—“Developing, Introducing, Retaining”, in order to shed some light on construction of Heilongjiang professional technicians.

We demonstrated a single-mode and biomolecule-induced tunable external cavity laser biosensor. This system achieves large dynamic range, high-Q resonance, and self-referencing through dual-mode lasing for high sensitivity label-free detection.

Gait is a particular locomotion pattern of human body. Analysis of gait parameters may help identify posture-related problems in people with injuries or diseases. In this work, biokinetic gyroscopes with wireless data transmission capability were used to record the right ankle angular rates during walking. A match filter and turns detection algorithm were used to measure the gait cadence and its subphases. Results of the experiments on a group of 16 healthy subjects demonstrated that the proposed method can detect the temporal gait parameters with a high degree of precision and reliably identify important gait events.

We characterized the uniformity and sensitivity of the distributed feedback laser biosensors in 96-well microplate format, with a thickness standard deviation of ∼35 nm. An assay was also used to demonstrate its biomolecule detection ability.

Photonic crystal enhanced fluorescence (PCEF) has been demonstrated as an effective technique for amplifying the electromagnetic excitation and emission extraction from surface-bound fluorescent molecules. Although optimal coupling of a fluorophore-exciting light source to the PC occurs with the use of collimated plane waves, PCEF surfaces are also capable of coupling light from focused sources but with a reduction in the obtainable enhancement factor. Using computer simulations and experimental measurements, we describe the interaction between the resonant bandwidth of a PCEF device surface and the optical design of the detection instrumentation that is used to provide fluorescence excitation. We show that highly collimated illumination is required for achieving the greatest PCEF enhancement factors, but at the expense of poor tolerance to non-uniformities in resonant wavelength across the PCEF surface. To overcome this limitation, we demonstrate a fixed wavelength/multiple incident angle scanning detection system that is capable of measuring every pixel in a PCEF fluorescence image under conditions that optimize resonant excitation efficiency.

With the development of HVDC project in State Strong Smart Grid, the Faraday magneto-optical effect optical current transformer has been paid more and more attention to. However, the signal to noise bands overlap in original Faraday effect DC optical current transformer causes its measurement accuracy to decrease. Therefore, this paper presents a Faraday magneto-optical effect DC optical sensing method based on modulation and demodulation. Moreover, a new Faraday effect DC optical current transformer measurement system is deduced and designed on this basis. Subsequently, this paper mainly studies and designs an AC modulated optical source. With data acquisition and analysis of several experiments by LabVIEW, the results prove that the optical source can steadily generate modulated light intensity. Based on the AC modulated optical source, combined with the DSP technology, a complete DC optical current measurement system is formed. The practicality of the designed DC optical current transformer system has been tested by experiments in this paper.

An intersection driving assistance system is developed, which focuses on improvement of traffic efficiency and driving comfort, while maintaining a high level of driving safety. The system can receive traffic light information through wireless communication, and assist the driver with driving support or warning information using received information on time-dependent traffic signal status. The paper describes the system structure, the implemented assistance strategy, which combines three main functions of passing support, violation warning and rear-end collision warning, and the system prototype that has been built. Field experiments show that the proposed assistance system and strategy can ensure a high level of traffic safety, while at the same time improving driving comfort and traffic efficiency at intersections.

With the development of State Strong Smart Grid, optical current transducer based on Faraday magneto-optical effect will become an ideal transducer to service the grid. However, due to the impact of temperature drift in practice, it can not work in the long-term stable situation. To solve the problem, the double closed-loop self-tuning method is proposed in this paper for the first time. This system includes two independent systems, the inner and outer loop system. It has theoretically demonstrated the mechanism how temperature drift affects the optical current transducer. And the mechanism has also been verified by a large number of experiments. At the same time, DSP system is used to analyze and process signals real timely. So the influence, caused by temperature drift, is offset, which will further enhance the measurement accuracy and operational stability of optical current transducer.

Time-dependent convection diffusion equation, with a discontinuous data and large Reynolds number, is examined. This kind of problem leads to interior layer phenomena due to the discontinuity. The solution changes rapidly near interior layer. Traditional finite volume method is applied. Two efficient numerical methods are constructed. One is Shishkin's finite volume method. Another is Improved-Shishkin's finite volume method. Shishkin's finite volume method applies Shishkin's idea to construct mesh partition. Improved-Shishkin's finite volume method applies multi-transition points technique to reconstruct mesh partition near interior layer. Numerical experiments indicate that both methods are well fitted the property of interior layer. Both methods are uniformly convergence scheme. Improved-Shishkin's finite volume method is more accurate than finite difference method, which is constructed by Farrell in his previous paper.

A wide variety of optical resonator structures have been used for label-free detection of chemical compounds, biomolecules, and cells, and several approaches have been developed commercially for application in life science research, environmental monitoring, quality control testing, and diagnostic testing. Label-free resonant optical sensors generally detect shifts in resonant wavelength or coupling angle caused by the interaction between the target molecule and the evanescent portion of resonant modes. Active resonator sensors, such as the distributed feedback laser (DFB) biosensor demonstrated in this work, have been drawing special interest because they generate their own narrow linewidth stimulated emission, while retaining simple light coupling instrumentation. Altering the refractive index (RI) of the media exposed to the DFB laser surface or surface adsorption of biomolecules changes the effective RI associated with the resonant mode, and results in modulation of the stimulated emission wavelength. The DFB laser sensor biosensor was fabricated with organic material on a flexible plastic substrate using a large surface-area nanoreplica molding process.

A distributed feedback laser has been demonstrated as a label free biosensor. The stimulated emission wavelength changes with the refractive index variations on the sensor surface. The sensor exhibits high resolution and wide dynamic range.

The antibacterial behaviour of ZnO nanopowder and their composite coatings were investigated against E. Coli. ZnO nanopowder and Aluminum based ZnO composite powders were synthesized using in-house powder processing techniques. Bacteria culture results showed that ZnO nanopowder and their composite powders displayed excellent bacteriostatic activity against E. coli. The antibacterial activity increased with increasing concentration of ZnO nanoparticle in their composite powders as well as increasing surface area of compacted pellets. These nanocomposite powders were subsequently used to generate antibacterial coatings using cold spray technology. The ratio of Al to ZnO in their composite powders were 80:20, 50:50 and 20:80 (wt.%). Micro structural characterization and phase analysis of feedstock powders and as-deposited coatings were carried out using FESEM/EDX and XRD. Antibacterial nanocomposite Al-ZnO coatings were successfully deposited using cold spraying parameters of 15 Bars at air temperature of between 200-300degC. These as- sprayed coatings of Al-ZnO composite powders with varying Al and ZnO ratios retained their inherent antibacterial property as verified from bacterial counting test. The results indicated that the antibacterial activity increased with increasing ZnO nanopowder concentration in the composite powder feedstock and cold sprayed coating.

Summary form only given. The fabrication of flexible, and optically transparent, arrays of microplasma devices having microcavities fabricated by a polymer-based, replica molding process is reported. This process enables arrays of microcavity plasma devices or microchannels with feature sizes as small as ~ 10 mum to be produced inexpensively and precisely over surface areas of at least tens of cm2. With the incorporation of a thin dielectric barrier coating within and around the microcavity, stable glow discharges are obtained without any degradation of the device or outgassing from surrounding polymeric materials. Devices having transparent electrodes and substrates (including glass and flexible plastic) have been operated successfully at rare gas pressures up to 800 Torr. Individual microplasma pixels with cross-sectional dimensions of 200 times 200 mum2 and 50 times 50 mum2, as well as plasma channels having widths of 20 mum and 150 mum and aspect ratios as large as 104:1, have been fabricated and tested. Hermetically sealed microplasma arrays with various microcavity shapes are successfully demonstrated for applications such as transparent displays, micro-reactors, and micro-fluidic cell detectors. Representative voltage-current data for these structures and lifetime measurements for a series of arrays are presented.

A new fusion model is proposed, which is the combination of integration BP neural networks models and D-S evidence reasoning model, to solve the problems of low precision rate in automotive engine fault diagnosis by traditional expert system. The method of this paper not only realizes feature level fusion of all subjective observation data and expert experiments on different parts of engineer, but also realizes the predominance compensation of different models. In simulation experiment, by comparison between the two methods, this method proposed in the paper can improve diagnosis precision 7.1%more than expert system and reduce time complication degree.

We report on the first microplasma devices with cavities that are fabricated on both rigid and flexible transparent substrates by a polymer-based replica molding process. The process enables accurate and inexpensive production of plasma pixels with dimensions an order of magnitude smaller than conventional plasma television pixels, large uniform pixel arrays, and channels of arbitrary shape. The replica molding process may be performed over large surface areas for applications including video display, heads-up displays, medical phototherapy, photopolymerization, and photonic circuit light sources

Impedance boundary conditions (IBC) relate electric and magnetic fields tangential to smooth material surfaces of highly conductive objects. The usage of IBC models in electromagnetic field simulators eliminates the need to model a scatterer's internal fields, thereby leaving only exterior scattering problems to be solved. In this paper, the time domain integral equation (TDIE) solver for analyzing scattering from non-transparent IBC objects is extended to analyze scattering from electrically thin, and potentially penetrable IBC surfaces. Two coupled TDIE that are very similar to those in Chen et al. (2004) are established and solved by marching-on-in-time (MOT). The proposed scheme is verified by means of several numerical examples.

A novel MOT temporal basis function designed for interpolating bandlimited signals, is proposed. The basis function proposed here derives from prolate spheroidal wave functions. It is shown that the interpolation error associated with the use of the proposed function can be made arbitrarily small, and decays exponentially fast as its duration and sampling rate increase. It is observed that for many reasonable choices of their construction parameters, the novel basis functions bear similarities to shifted Lagrange interpolating polynomials. The proposed basis function's principal advantage over shifted Lagrange interpolating polynomials arises in the context of the low-frequency TDIE solvers as the interpolated signals derived from it are automatically bandlimited.

PWTD (plane wave time domain) formulations that arise from nonuniform and uniform sampling of transient plane wave patterns are presented and their advantages and disadvantages discussed. In addition, a hybrid scheme that optimally leverages the advantages of both sampling schemes across PWTD levels within a multilevel framework is presented. This hybrid scheme is argued to be especially suitable for parallel implementation. The accuracy of the proposed hybrid scheme is verified by a numerical example.

Fundamental to progress in integrated optical systems are techniques for controlling light propagation on small spatial scales. The development of photonic band gap (PBG) waveguides (Joannopoulos, J.D. et al., 1982) represents a major step towards achieving such control, as it permits the nearly lossless redirection of light flows through sharp waveguide bends, a feat unachievable using conventional optical waveguide structures. Recently, a new kind of optical waveguide was introduced that exploits the existence of surface plasmon polaritons (SPP) on metals in the optical regime to construct surface-based PBG structures (Kitson, S.C. et al., Phys. Rev. Lett., vol.77, p.2670-3, 1996; Bozhevolnyi, S.I., Phys. Rev. Lett., vol.86, p.3008-10, 2001). These SPPBG waveguide structures introduce interesting mechanisms for controlling light flow beyond the possibilities offered by conventional PBG waveguides. Notable experimental progress in the construction and characterization of SPPBG waveguides notwithstanding few efforts, to date, have been directed at their theoretical/computational analysis. Here, we report on the implementation of a three-dimensional (3D) finite difference time domain (FDTD) scheme for simulating wave propagation in SPPBG waveguides. In addition, two specific SPPBG bent waveguide geometries are analyzed.