Asymmetrical Fabry-Perot cavity slot micro-ring resonator and its sensing characteristics

To achieve high quality factor and high-sensitivity refractive index sensor,a slot micro-ring resonator(MRR)based on asymmetric Fabry-Perot(FP)cavity was proposed.The structure consisted of a pair of elliptical holes to form an FP cavity and a microring resonator.The two different optical modes generated by the micro-ring resonator were destructively interfered to form a Fano line shape,which improved the system sensitivity while obtaining a higher quality factor and extinction ratio.The transmission principle of the structure was analyzed by the transfer matrix method.The transmission spectrum and mode field distribution of the proposed structure were simulated by the finite difference time domain(FDTD)method,and the key structural parameters affecting the Fano line shape in the device were optimized.The simulation results show that the quality factor of the device reached 22037.1,and the extinction ratio was 23.9 dB.By analyzing the refractive index sensing characteristics,the sensitivity of the structure was 354 nm·RIU−1,and the detection limit of the sensitivity was 2×10−4 RIU.Thus,the proposed compact asymmetric FP cavity slot micro-ring resonator has obvious advantages in sensing applications owing to its excellent performance.

A Low-dimensional Illumination Space Representation of Human Faces for Arbitrary Lighting Conditions

The proposed method for low-dimensional illumination space representation (LDISR) of human faces can not only synthesize a virtual face image when given lighting conditions but also estimate lighting conditions when given a face image. The LDISR is based on the observation that 9 basis point light sources can represent almost arbitrary lighting conditions for face recognition application and di?erent human faces have a similar LDISR. The principal component analysis (PCA) and the nearest neighbor clustering method are adopted to obtain the 9 basis point light sources. The 9 basis images under the 9 basis point light sources are then used to construct an LDISR which can represent almost all face images under arbitrary lighting conditions. Illumination ratio image (IRI) is employed to generate virtual face images under diffierent illuminations. The LDISR obtained from face images of one person can be used for other people. Experimental results on image reconstruction and face recognition indicate the e?ciency of LDISR.

PLASMA RESONANCE FIBER OPTIC SENSOR FOR CURE MONITORING OF EPOXY COMPOSITE

The plasma resonance fiber optic sensor has a research values in theory and is widely used in engineering because of its simple structure and high sensitivity. It is a simple and sensitive method to measure the refractive index with optical fiber plasma wave. We make use of this characteristic to manufacture the plasma resonance fiber optic sensor which can detect the cure of epoxy compo site. We study the method of testing the solutions which have different refractive index with plasma resonance fiber optic sensor. A fiber optic sensing probe which has reliable performance and convenient operation for detecting the refractive index has been designed. The system for detecting the solution refractive index is developed and used to measure the refractive index of epoxy during the different phases in the cure process. Result shows that this system is credible and stable, the parameters tested are in accord with the facts.

Malignancy and mortality in a population-based cohort of patients with coeliac disease or ‘gluten sensitivity’

AIM: To determine the risk of malignancy and mortality in patients with a positive endomysial or anti-gliadin an- tibody test in Northern Ireland. METHODS: A population-based retrospective cohort study design was used. Laboratory test results used in the diagnosis of coeliac disease were obtained from the Regional Immunology Laboratory, cancer statistics from the Northern Ireland Cancer Registry and mortal- ity statistics from the General Registrar Office, Northern Ireland. Age standardized incidence ratios of malignant neoplasms and standardized mortality ratios of all-cause and cause-specific mortality were calculated. RESULTS: A total of 13 338 people had an endomysial antibody and/or an anti-gliadin antibody test in Northern Ireland between 1993 and 1996. There were 490 pa- tients who tested positive for endomysial antibodies and they were assumed to have coeliac disease. There were 1133 patients who tested positive for anti-gliadin anti- bodies and they were defined as gluten sensitive. Ma- lignant neoplasms were not significantly associated with coeliac disease; however, all-cause mortality was signifi- cantly increased following diagnosis. The standardized incidence and mortality ratios for non-Hodgkin’s lym- phoma were increased in coeliac disease patients but did not reach statistical significance. Lung and breast cancer incidence were significantly lower and all-cause mortal-ity, mortality from malignant neoplasms, non-Hodgkin’s lymphoma and digestive system disorders were signifi- cantly higher in gluten sensitive patients compared to the Northern Ireland population. CONCLUSION: Patients with coeliac disease or gluten sensitivity had higher mortality rates than the Northern Ireland population. This association persists more than one year after diagnosis in patients testing positive for anti-gliadin antibodies. Breast cancer is significantly re- duced in the cohort of patients with gluten sensitivity.

How to realize a negative refractive index material at the atomic level in an optical frequency range?

The theoretical mechanism for realizing a negative refractive index material in an optical frequency range with an atomic gas system of electromagnetically induced transparency (EIT) is studied. It is shown that under certain conditions such a dense gas can exhibit simultaneously negative permittivity and negative permeability, and negligibly small loss.

Measurement of refrative index based on fiber Mach-Zehnder interference

In order to detect the refractive index of liquid with high precision,based on modular interference,Mach-Zehnder optical fiber refractive rate sensor was studied.Sensor structure is composed of ordinary single-mode fiber and multimode fiber,according to the singlemode multimode singlemode sequence to fuse together,and the fused optical fiber is used to process the taper.As a result,the diameter of the sensing head is about 10μm.Experimental results show that,as liquid refractive index increases range from 1.33 to 1.35,the loss peak of the transmission spectrum will shift to long wave direction.

Optical Fiber Pressure Sensor with Reference Channel

The principle of optical fiber pressure sensing probe with common diaphragm and the method for stabilizing the laser diodes are described in this paper at first.Then we discussed the improvement in characteristics of the system by means of taking the techniques of reference light channel and ratio measurement.

Portable Instrument for Normalized Difference Vegetation Index

By using four specially designed narrow bandpass filters and photodetectors in the instrument, the incident and reflected radiances of sun light on the vegetation are optically sensed, at the red and near infrared bands, then the normalized difference vegetation index(NDVI) is processed by a microprocessor. Compared with conventional spectrometer measuring method of NDVI, the instrument is easy to be used, compact, light and low-cost.

Remote Sensing Image Segmentation with Probabilistic Neural Networks

This paper focuses on the image segmentation with probabilistic neural networks (PNNs). Back propagation neural networks (BpNNs) and multi perceptron neural networks (MLPs) are also considered in this study. Especially, this paper investigates the implementation of PNNs in image segmentation and optimal processing of image segmentation with a PNN. The comparison between image segmentations with PNNs and with other neural networks is given. The experimental results show that PNNs can be successfully applied to image segmentation for good results.

Novel shape detection systems based on FBG sensor net for intelligent endoscope

This dissertation aims at providing steady sensing for the shape detection of colonoscopes. The research especially deals with the key techniques of fiber bragg grating (FBG) large curvature sensor and sensor net, integrates the techniques of mechatronics and computer graphics, and develops real time FBG shape sensing system and incremental shape sensing system for colonoscopies.

Nonlinear Optical Susceptibility and Refractive Index of Two Polyaniline Families

By use of the Keldysh non-equilibrium Green’s-function methods, the third harmonic susceptibilities of two polyaniline families, PANI-HCl and PANI-H 3PO 4, are calculated [ x (3) ( ω )≈10 -12 esu]. It was found that the third harmonic susceptibility of polyaniline strongly depends on the delocalization of the electrons. The refractive indices n ( λ =589 nm) of PANI-HCl and PANI-H 3PO 4 are calculated by use of three common methods (the Lorentz-Lorentz theoretical model, the Gladstone-Dale group contribution and the Vogel group correlation) based on group contributions to molar refraction. The calculated n values are varied from 1.31 to 1.42 for PANI-HCl and 1.36 to 1.45 for PANI-H 3PO 4.

Atmospheric correction of ocean color imagery over turbid coastal waters using active and passive remote sensing

This paper demonstrates an atmospheric correction method to process MODIS/Aqua (Moderate-resolution Imaging Spectroradiometer) ocean color imagery over turbid coastal waters with the aid of concurrent CALIOP (Cloud-Aerosol LIdar with Orthogonal Polarization) aerosol data, assuming that there exists "nonturbid" water in the study area where MODIS aerosol optical properties can be retrieved accurately. Aerosol properties from CALIOP measurements were obtained and related to those from MODIS. This relationship, combined with CALIOP aerosol data, was extended to turbid water to derive MODIS aerosol properties, where atmospheric correction using MODIS data alone often fails. By combining MODIS and CALIOP data, aerosol signals were separated from the total signals at the satellite level, and water-leaving radiances in turbid waters were subsequently derived. This method was tested on several MODIS/Aqua ocean color images over South China turbid waters. Comparison with field data shows that this method was effective in reducing the errors in the retrieved water-leaving radiance values to some extent. In the Zhujiang (Pearl) River Estuary, this method did not overestimate the aerosol effects as severely, and provided far fewer negative water-leaving radiance values than the NASA (National Aeronautics and Space Administration) default methods that used MODIS data alone.

A Thin Cloud Removal Method from Remote Sensing Image for Water Body Identification

In this paper,a thin cloud removal method was put forward based on the linear relationships between the thin cloud reflectance in the channels from 0.4 μm to 1.0 μm and 1.38 μm.Channels of 0.66 μm,0.86 μm and 1.38 μm were chosen to extract the water body information under the thin cloud.Two study cases were selected to validate the thin cloud removal method.One case was applied with the Earth Observation System Moderate Resolution Imaging Spectroradiometer(EOS/MODIS) data,and the other with the Medium Resolution Spectral Imager(MERSI) and Visible and Infrared Radiometer(VIRR) data from Fengyun-3A(FY-3A).The test results showed that thin cloud removal method did not change the reflectivity of the ground surface under the clear sky.To the area contaminated by the thin cloud,the reflectance decreased to be closer to the reference reflectance under the clear sky after the thin cloud removal.The spatial distribution of the water body area could not be extracted before the thin cloud removal,while water information could be easily identified by using proper near infrared channel threshold after removing the thin cloud.The thin cloud removal method could improve the image quality and water body extraction precision effectively.

Abundance quantification by independent component analysis of hyperspectral imagery for oil spill coverage calculation

The estimation of oil spill coverage is an important part of monitoring of oil spills at sea.The spatial resolution of images collected by airborne hyper-spectral remote sensing limits both the detection of oil spills and the accuracy of estimates of their size.We consider at-sea oil spills with zonal distribution in this paper and improve the traditional independent component analysis algorithm.For each independent component we added two constraint conditions:non-negativity and constant sum.We use priority weighting by higher-order statistics,and then the spectral angle match method to overcome the order nondeterminacy.By these steps,endmembers can be extracted and abundance quantified simultaneously.To examine the coverage of a real oil spill and correct our estimate,a simulation experiment and a real experiment were designed using the algorithm described above.The result indicated that,for the simulation data,the abundance estimation error is 2.52% and minimum root mean square error of the reconstructed image is 0.030 6.We estimated the oil spill rate and area based on eight hyper-spectral remote sensing images collected by an airborne survey of Shandong Changdao in 2011.The total oil spill area was 0.224 km^2,and the oil spill rate was 22.89%.The method we demonstrate in this paper can be used for the automatic monitoring of oil spill coverage rates.It also allows the accurate estimation of the oil spill area.

Effect of Rust Disease on Photosynthetic Rate of Wheat Plant

The purpose of this research was to study the influence of rust diseases on photosynthetic rate of the created local varieties and introduced variety samples of wheat. Experiment was carried out with two variants-control and 25% Tilt treatment. The 25% solution of Tilt was used to prevent disease infection. The photosynthetic rate was measured by T-type URAS-2 infrared gas analyzer （made＇ in Germany）. Disease infection rate was determined based on the Cobby balling scale. Ontogenetic and daily rate of photosynthesis by effect of the disease were decreased. The amount of assimilated CO2 during the day and vegetation period linearly depends on the disease infection degree. At the same time, the activation of non-infected parts＇ photosynthetic rate of some varieties was observed. The difference reaches up to 87% between the variants as a result of the rapid aging of photosynthesis apparatus.

Comparison of modelled-and remote sensing-derived daily snow line altitudes at Ulugh Muztagh,northern Tibetan Plateau

The ice cap Ulugh Muztagh in the central Kunlun Shan at the northern fringe of the Tibetan Plateau is a very isolated region with arid cold conditions. No observational, meteorological or glaciological ground truth data is available. Using the Moderate-resolution Imaging Spectroradiometer(MODIS) Level 1 radiance Swath Data(MOD02QKM) with a spatial resolution of 250 m, transient snow lines during the months of July to September in 2001 to 2014 are derived. Results are used to calibrate the physical based Coupled Snowpack and Ice surface energy and Mass balance model(COSIMA). The model runs on a representative detail region of Ulugh Muztagh(UM) on a digital elevation model with the same spatial resolution as the MODIS bands. In the absence of field observations, the model is driven solely by dynamically downscaled global analysis data from the High Asia Refined analysis(HAR). We compare remote sensing derived and modelled mean regional transient snow line altitudes in the course of consecutive summer seasons in 2008 to 2010. The resulting snow line altitude(SLA) and annual equilibrium line altitude(ELA) proxy of both methods coincide very well in their interannual variability in accordance with interannual variability of climatic conditions. Since SLAs of both methods do notconsistently agree on a daily basis a usage of remote sensing derived SLAs for model calibration in the absence of field observation data is only limitedly feasible for daily analysis. ELA approximation using the highest SLA at the end of ablation period may not be applied to UM because the negative winter mass balance(MB) is not reflected in the summer SLA. The study reveals moderate negative MB for UM throughout the modelling period. The mean regional MB of UM accounts for-523±410 mm w.e. a-1 in the modelling period. Hence UM seems not to belong to the area of the ‘Karakorum anomaly' comprising a region of positive mass balances in recent years which has its centre presumably in the Western Kunlun Shan.

Using Support Vector Regression to Analyze Urban Atmosphere Pollution with Optical Remote Sensing Data

The concentration of absorbable particulate matter less than 10 μm termed as PM10 is the most important urban air pollution index for air quality monitoring. This paper presents a space based PM10 monitoring algorithm based on QUAC （QUick atmosphere correction） for optical remote sensing data and SVR （support vector regression）. PM 10 concentration measurements from nine ground based stations in Hangzhou, China and the MODIS （moderate-resolution imaging spectroradiometer） images were analyzed. Experimental result indicates that the correlation between CD （correction differences） with actual measured data is better than correlation between AOD （aerosol optical depth） with measured data. In addition, the fitting performance of the SVR model established with CD and measured data is better than traditional regression models.

Remote sensing retrieval of total absorption coefficient in the Bohai Sea

Temporal and spatial patterns of inherent optical properties in the Bohai Sea are very complex. In this paper, we used 77 groups of field data of AOPs （apparent optical properties） and IOPs （inherent optical properties） collected in June, August, and September of 2005 in the Bohai Sea, to retrieve the spectral total absorption coefficient a（2） with the quasi-analytical algorithm （QAA）. For QAA implementation, different bands in the region 680-730 nm （in 5 nm intervals） were selected and compared, to determine the optimal band domain of the reference wavelength. On this basis, we proposed a new algorithm （QAA-Com）, a combination of QAA-685 and QAA-715, according to turbidity characterized by a（440）. The percentage difference of model retrievals in the visible domain was between 4.5%-45.1%, in average of 18.8% for a（2）. The QAA model was then applied to Medium Resolution Imaging Spectrometer （MERIS） radiometric products, which were temporally and spatially matched with in-situ optical measurements. Differences between MERIS retrievals and in-situ values were in the range 9.2%-27.8% for a（2） in the visible domain. Major errors in satellite retrieval are attributable to uncertainties of QAA model parameters and in-situ measurements, as well as imperfect atmospheric correction of MERIS data by the European Space Agency （ESA）. During a storm surge in April 2009, time series of MERIS images together with the QAA model were used to analyze spatial and temporal variability of the total absorption coefficient pattern in the Bohai Sea. It is necessary to collect more independent field data to improve this algorithm.

Experimental and Theoretical Analysis of an Optical Current Sensor for High Power Systems

A magneto-optical sensor, using a dual quadrature polarimetfic processing scheme, was evaluated for current metering and protection applications in high voltage lines. Sensor calibration and resolution were obtained in different operational conditions using illumination in the 1550-nm band. Results obtained indicated the feasibility of interrogating such sensor via the optical ground wire （OPGW） link installed in standard high power grids. The polarimetric bulk optical current sensor also was theoretically studied, and the effects of different sources of error considering practical deployment were evaluated. In particular, the interference from external magnetic fields in a tree-phase system was analyzed.

Land cover classification of remote sensing imagery based on interval-valued data fuzzy c-means algorithm

There is a certain degree of ambiguity associated with remote sensing as a means of performing earth observations.Using interval-valued data to describe clustering prototype features may be more suitable for handling the fuzzy nature of remote sensing data,which is caused by the uncertainty and heterogeneity in the surface spectral reflectance of ground objects.After constructing a multi-spectral interval-valued model of source data and defining a distance measure to achieve the maximum dissimilarity between intervals,an interval-valued fuzzy c-means(FCM)clustering algorithm that considers both the functional characteristics of fuzzy clustering algorithms and the interregional features of ground object spectral reflectance was applied in this study.Such a process can significantly improve the clustering effect;specifically,the process can reduce the synonym spectrum phenomenon and the misclassification caused by the overlap of spectral features between classes of clustering results.Clustering analysis experiments aimed at land cover classification using remote sensing imagery from the SPOT-5 satellite sensor for the Pearl River Delta region,China,and the TM sensor for Yushu,Qinghai,China,were conducted,as well as experiments involving the conventional FCM algorithm,the results of which were used for comparative analysis.Next,a supervised classification method was used to validate the clustering results.The final results indicate that the proposed interval-valued FCM clustering is more effective than the conventional FCM clustering method for land cover classification using multi-spectral remote sensing imagery.