Insensitive Band Research Articles

Margin-based approach for outlier detection of industrial design data using a modified general regression neural network

AbstractThe choice of components in industrial design involves setting design parameters that typically must reside inside permissible ranges called “design margins”. This paper proposes a novel automated method called the Margin-Based General Regression Neural Network (MB-GRNN) that classifies design errors for design parameters that are outside of permissible ranges as outliers, directly from industrial design data, using an unsupervised machine learning approach. The method is based on a modified GRNN that estimates extremal margin boundaries of design parameters by self-learning the features from datasets. These extremal permissible margin boundaries are determined by “stretching out” the upper and lower GRNN surfaces using an iterative application of stretch factors (a second kernel weighting factor). The method creates a variable insensitive band surrounding the data cloud, interlinked with the normal regression function, providing upper and lower margin boundaries. These boundaries can then be used to determine outliers and to predict a range of permissible values of design parameters during design. Pushing out extremal margin boundaries reduce the false identification of outliers. This classification technique could be used by industrial engineers to detect likely outliers and to predict a range of permissible output limits for chosen design parameters. The efficacy of this method has been validated against the widespread Parzen window method by comparing experimental results from three multivariate datasets. It was found that the two methods have different but complementary capabilities. The MB-GRNN also uses a modified algorithm for estimating the smoothing parameter using a combination of clustering, k-nearest neighbor, and localized covariance matrix.

Evanescent wave induced polarization-insensitive self-organization of stratified single-negative materials

Optical fields can induce optical forces between macroscopic objects, giving rise to different structures. Through rigorous calculation, we show that a collection of single negative slabs which possesses either negative permittivity or negative permeability (i.e. ε < 0, μ > 0 or ε > 0, μ < 0) in water can be self-organized into one-dimensional photonic crystals, due to the coupling of propagating wave and evanescent wave. We further demonstrated that the optical binding is irrespective of the polarization and angle of the incident plane wave. We call such a phenomenon—polarization-insensitive optical binding. We also demonstrate that polarization-insensitive optical binding can be achieved on microscale and millimeter scale. Polarization and angle insensitive band edge is the key to achieve polarization and angle insensitive optical binding. This work provides a new strategy to tailor the photonic crystals containing single negative materials towards the development of fine-tuning optical devices.

Up-conversion emission thermometry for semiconductor laser cooling

The ability to precisely measure temperature is critical to eventually developing semiconductor-based optical refrigerators. Presently, a number of approaches exist for conducting contactless temperature measurements. They are mainly based on the temperature-dependent optical response of materials. A common approach called pump–probe luminescence thermometry (PPLT) uses temperature-dependent shifts of a material’s band edge emission energy to assess temperature. PPLT, however, cannot be reliably applied to materials such as CsPbBr3 nanocrystals, which exhibit temperature insensitive band gaps. To overcome this restriction, we have developed a new optical thermometry based on temperature-dependent changes to below gap-excited (anti-Stokes, ASPL) and above gap-excited (Stokes, PL) photoluminescence intensity ratios (i.e. IASPL/IPL). In it, IASPL/IPL can be used to assess local temperature due to the exponentially sensitive nature of emission up-conversion efficiencies. The developed thermometry is not unique to CsPbBr3 and can be applied other systems found suitable for demonstrating semiconductor-based laser cooling.

Study on influencing factors of prediction accuracy of support vector machine (SVM) model for NOx emission of a hydrogen enriched compressed natural gas engine

In recent years, support vector machine (SVM) method has been rapidly developed because of its great advantage in solving small sample regression problems. Based on the prediction accuracy of NOx emission, the SVM method is applied to the regression analysis of the steady-state calibration experimental results of a hydrogen enriched compressed natural gas (HCNG) engine in this research article. The effects of the model parameters (penalty factor kernel, function width and insensitive band loss function) and the training sample size on the prediction accuracy of the regression model are studied. Results show that both model parameters and training sample size can influence the prediction accuracy of the SVM model. Additionally, the method of determining the optimal SVM regression model is also summarized. The optimal SVM regression model is obtained by the manifold absolute pressure (MAP) and the fuel equivalence ratio (θ) halved sample, with the training sample size of 270 for the experimental data used in this study. Results show that the optimal SVM regression model can decrease the predicted mean absolute percentage error (MAPE) and the maximum relative prediction error (MRE) of the brake specific NOx emission greatly, from 12.54% to 8.32% and 56.66% to 25.89%, respectively. It indicates that the prediction performance can be improved apparently by the method promoted in the paper, which provides a new perspective for the further application of SVM method in the field of automobile engines calibration.

Efficient recycling of trapped energies for dual-emission in Mn-doped perovskite nanocrystals

Doping impurity into semiconductor nanocrystals (NCs) is able to create novel optical, electronic, and magnetic functionalities. Recently, dual-emissions from Mn-doped lead chloride perovskites NCs have attracted much attention. However, the mechanisms of doping and energy-transfer to Mn ions of the perovskite NCs are still unclear. In this work, through the newly-developed post-treatment methods, it is found that excess Cl- can boost the Mn-emission due to the efficient ion diffusion and exchanges during Mn-doping processes. Importantly, a clear slow energy accumulation in the Mn dopants with time constant of ~ 200 ns is revealed from time-resolved photoluminescence (PL) measurements. Together with the doping insensitive band edge PL, these results indicate that the Mn dopants should snatch the energy from non-radiative trap states rather than from band states, which implies an efficient recycling of trapped nonradiative energy for luminescence by the dopants. The developed efficient doping method and proposed mechanism of energy transfer would provide unique insights into the mechanisms of doping. Moreover, fundamental investigations on nanostructure and optical properties are expected to increase its potential in electronic or magnetic applications.

Analysis of spectral difference between the foreside and backside of leaves in yellow rust disease detection for winter wheat

Disease detection by means of hyperspectral reflectance is inevitably influenced by the spectral difference between foreside (adaxial surface) and backside (abaxial surface) of a leaf. Taking yellow rust disease in winter wheat as an example, the spectral differences between the foreside and backside of healthy and diseased wheat leaves at both jointing stage and grain filling stage were investigated based on spectral measurements with a large sample size. The spectral difference between leaf orientations was found to be confused with disease signals to some extent. Firstly, the original bands and spectral features (SFs) that were sensitive to the disease were identified through a correlation analysis. Then, to eliminate the influence of leaf orientation, a pairwise t test was used to screen for the orientation insensitive bands and SFs. By conducting an overlapping procedure, the bands/SFs that were sensitive to the disease yet insensitive to the leaf orientations were selected and tested for disease detection. The results suggested that the Ref525–745 nm, Ref1060–1068 nm, DEP920–1120, DEP1070–1320, AREA1070–1320, SR and NDVI at the jointing stage, and the Ref606–697 nm, Ref740–752 nm, WID550–770, SR, NDVI, GNDVI, RDVI, GI and MCARI at the grain filling stage were capable of eliminating the influence of leaf orientation, and were retained for disease detection. Given these features, models based on the partial least square regression analysis showed a better performance at the grain filling stage, with the R 2 of 0.854 and RMSE of 0.104. This result indicated that reliable estimation of disease severity can be made until the grain filling stage. In the future, more attention should be given to leaf orientation when detecting disease at the canopy level.

GaAsBi atomic surface order and interfacial roughness observed by STM and TEM

GaAsBi is an interesting ternary material for opto-electronic applications. Bi fractions of 11-13% allow 1.55 μm emissions from a range of bulk and QW structures. GaAsBi has shown strong room temperature photoluminescence. The temperature insensitive band gap and large spin orbit splitting are attractive optoelectronic features, however the typical full width half maximum is 2.5 times greater than GaAs. In solid source molecular beam epitaxy (MBE), near stoichiometric fluxes and low growth temperatures are necessary to achieve the desired Bi content. In order to explore photoluminescence linewidth broadening and the accommodation of strain a joint scanning tunnelling microscopy (STM) and scanning transmission electron microscopy (STEM) study of quasi-bulk and QW structures has been undertaken.

Study on O-Terphenyl/Polystyrene Blends: How Plasticizer Affects the Glass Transition of Polystyrene?

The effect of plasticizer o-terphenyl on the glass transition of polystyrene was investigated by Fourier transform infrared spectroscopy from a new aspect. The peak areas of four conformation insensitive bands as a function of temperature were studied, these being assigned to the vibrational modes of main chain groups and side groups of polystyrene. It was shown that the reorientation relaxation temperature of the main chain around glass transition was lower than that of the side groups when polystyrene was plasticized by o-terphenyl. It was explained on the basis of cohesional entanglements of polystyrene chains. The reorientation relaxation region of the side groups was nearly the same as the macroscopically observable glass transition region of polystyrene, implying that the glass transition process of polystyrene was dominated by the reorientation of side groups.

Frequency analysis of wavefront curvature sensing: optimum propagation distance and multi-z wavefront curvature sensing

In this paper we determine the optimum propagation distance between measurement planes and the plane of the lens in a wavefront curvature sensor with the diffraction optics approach. From the diffraction viewpoint, the measured wavefront aberration can be decomposed into Fourier harmonics at various frequencies. The curvature signal produced by a single harmonic is analyzed with the wave propagation transfer function approach, which is the frequency analysis of wavefront curvature sensing. The intensity of the curvature signal is a sine function of the product of the propagation distance and the squared frequency. To maximize the curvature signal, the optimum propagation distance is proposed as one quarter of the Talbot length at the critical frequency (average power point at which the power spectrum density is the average power spectrum density). Following the determination of the propagation distance, the intensity of the curvature signal varies sinusoidally with the squared frequencies, vanishing at some higher frequency bands just like a comb filter. To cover these insensitive bands, wavefront curvature sensing with dual propagation distances or with multi-propagation distances is proposed.

A spectral index to monitor the head-emergence of wheat in semi-arid conditions

Harvesting wheat ( Triticium aestivum L.) for forage or leaving it for grain is the main decision uncertainty growers face in semi-arid regions during mid-season. To facilitate decision-making, a decision support system (DSS) has recently been proposed that requires information about crop water and nutritional status during spike emergence. Though remote sensing has been used to provide site-specific crop status information, a spectral vegetation index is needed to ensure that the information has been acquired during spike emergence. The objective of this study was to propose a spectral index sensitive to spike emergence and validate its suitability across different commercial farm fields by using ground spectral measurements and multispectral satellite imagery. To develop the index, controlled experiments with commonly grown wheat varieties were conducted during the 2004/2005 and 2005/2006 growing season in the agricultural area of the northern Negev desert of Israel. The experiments showed that spike emergence correlated most strongly ( r = 0.7, p < 0.05) with spectral changes near the 1.2 μm water absorption feature in contrast to the band at 1.1 μm which appeared to be only weakly correlated. Thus, the spike emergence sensitive band at 1.2 μm has been combined with the insensitive band at 1.1 μm as reference to form the ratio-based normalized heading index (NHI). Experimental data were then used to establish an index threshold that helps separate data acquired before and after spike emergence. The proposed NHI was able to identify spike emergence with a classification accuracy varying between 53 and 83%. Accuracy was influenced by season, and whether narrow or broad spectral bands were used. Validation of the index in commercial farm fields in Israel and the United States showed that the classification accuracy was similar for ground spectral measurements and the advanced land imager (ALI) satellite imagery. These results suggest that the NHI is suited for identifying the onset of heading throughout wheat-growing areas without the need for characterizing seasonal trends.

Multiband drought index enhances soil and vegetation moisture monitoring

Drought, the most complex and least understood of all natural hazards, also affects more people than any other.1 Traditional drought monitoring is based on observations at specific locations, and thus lacks continuous spatial coverage. Satellite remote sensing offers an effective means to continuously monitor drought across wide areas. Most drought monitoring from space observes vegetation moisture using spectral indices that reflect variations in the spectral signatures caused by water stress. Very few studies focus on equivalent soil-moisture monitoring, however. Simple spectral indices allow interpretation of changes in vegetation water content using a normalized ratio of a sensitive and an insensitive band. Uncertainties arise because these indices cannot completely remove background soil effects. The reflectance of a canopy is strongly influenced by the background soil reflectance, which is primarily determined by the moistness of the soil surface at a given location. Therefore, soil moisture must be taken into account in drought analysis. We performed sensitivity studies of three short-wave IR (SWIR) bands of the Moderate Resolution Imaging Spectroradiometer (MODIS) and observed that the reflectance of each SWIR band responds differently to variations in soil and vegetation moisture.2 We therefore defined the Normalized Multiband Drought Index (NMDI),

Sensitivity studies of the moisture effects on MODIS SWIR reflectance and vegetation water indices

The effects of soil moisture and leaf water content on canopy reflectance of MODIS shortwave infrared (SWIR) bands 5, 6, and 7 and water‐related indices are studied quantitatively using the coupled soil–leaf–canopy reflectance model. Canopy spectra simulations under various input conditions show that soil moisture has a large effect on each SWIR reflectance at low leaf area index (LAI) values, among which band 5 is the most sensitive to soil moisture variations, while band 7 responds strongest to dry soil conditions. Band 5 is also better suited to measure leaf water content change, since it obtains a higher variation when leaf water content changes from dry to wet. In general, each SWIR band responds to soil moisture and leaf water content differently. By using the normalized calculation between the water absorption‐sensitive band and insensitive band, the Normalized Difference Water Index shows the most capability to remove the soil background effect and enhance the sensitivity to leaf water content. These two moisture variables may be separated by combining multiple rather than one SWIR band with a near‐infrared band considering that each SWIR band has a different response to soil moisture and leaf water content.

A New Reflectance Index for Remote Sensing of Chlorophyll Content in Higher Plants: Tests using Eucalyptus Leaves

Summary The visible/near infrared reflectance properties of leaves from several Eucalyptus species were studied to determine appropriate indices for remote sensing of chlorophyll content. Reflectance near 710 nm wavelength showed a higher sensitivity to chlorophyll content than reflectance near 550nm. The near infrared band with the least sensitivity to chlorophyll content was located at 850 nm. The use of R710 nm as the sensitive band and R850 nm as the insensitive band, increased the correlation of the reflectance indices to chlorophyll content. Among several reflectance indices tested, the ratio (R850-R710)/(R850-R680) performed best, and is proposed as a new index for the remote estimation of chlorophyll content in higher plants. This new index is insensitive to the effects of leaf scattering on reflectance, and relates strongly to the variation in reflectance caused by chlorophyll absorption.

Simple methods for assessing the conformational sensitivity of infrared bands by dichroism

AbstractIn characterizing the overall orientation of polymers by infrared (IR) dichroism, the orientation function must be obtained from the dichroic ratios of conformationally insensitive bands. Identification of such bands is thus necessary prior to the calculation of the orientation function. In this study, we devise two simple methods for evaluating the conformational sensitivities of IR bands from the measurement of the dichroic ratio. Both methods are based on the fact that the orientation function calculated by all conformationally insensitive bands should be identical, while this is not true for conformationally sensitive bands. Poly(ether ether ketone) (PEEK) is used as an example to demonstrate the use of these methods.

Novel GTP-binding proteins in plasma membranes of the fungus [formula omitted

We report the existence of several families of GTP-binding proteins in plasma membranes of Metarhizium anisopliae . Two proteins (18.4 and 24 kDa) resemble mammalian Gn-proteins in their being toxin insensitive, binding [α- 32P]GTP on nitrocellulose blots of sodium dodecyl sulfate (SDS)-polyacrylamide gels, and also in their immunological properties. Four other proteins (31–38.2 kDa) were similar except that they did not bind [α- 32P]GTP after treatment with sodium dodecyl sulfate. An 18.2 kDa cholera toxin substrate and three toxin insensitive bands (18.6, 18.8, and 24 kDa) are novel proteins antigenically related both to mammalian G-proteins and ras gene products. An additional 23 kDa pertussis toxin substrate (the major G-protein in a crude mycelial extract) reacted strongly with antisera to G-proteins but not with anti- ras serum. Other substrates ADP ribosylated by cholera toxin or botulinum D toxin were immunologically unreactive. Analysis of the structural and functional characteristics of these multiple GTP-binding proteins will promote a better understanding of signal transduction in fungi.

Terminal protein association and sequence homology in linear mitochondrial plasmid-like DNAs of sorghum and maize

The linear extrachromosomal mitochondrial plasmid-like DNAs from the Ru cytoplasm of maize, and M35-1 and IS1112C cytoplasms of sorghum, possess 5' terminally-attached proteins. These molecules required proteinase K treatment for mobility in agarose gels and were susceptible to exonuclease III but not lambda exonuclease cleavage. Hybridizations, under stringent conditions, indicated that the sorghum plasmid-like DNAs, N1 and N2, did not possess DNA sequence homology to cloned central regions of S1 and S2, the linear mitochondrial plasmid-like DNAs present in S cytoplasm of maize. In addition, a novel 4.2kb, DNAase sensitive, RNAase insensitive band, exhibiting homology to internal sequences from maize S2, was observed in the sorghum IS1112C cytoplasm only.