Fusion of Region Extraction and Cross-Entropy SVM Models for Wheat Rust Diseases Classification

Wheat rust diseases are one of the major types of fungal diseases that cause substantial yield quality losses of 15%–20%every year.The wheat rust diseases are identified either through experienced evaluators or computerassisted techniques.The experienced evaluators take time to identify the disease which is highly laborious and too costly.If wheat rust diseases are predicted at the development stages,then fungicides are sprayed earlier which helps to increase wheat yield quality.To solve the experienced evaluator issues,a combined region extraction and cross-entropy support vector machine(CE-SVM)model is proposed for wheat rust disease identification.In the proposed system,a total of 2300 secondary source images were augmented through flipping,cropping,and rotation techniques.The augmented images are preprocessed by histogram equalization.As a result,preprocessed images have been applied to region extraction convolutional neural networks(RCNN);Fast-RCNN,Faster-RCNN,and Mask-RCNN models for wheat plant patch extraction.Different layers of region extraction models construct a feature vector that is later passed to the CE-SVM model.As a result,the Gaussian kernel function in CE-SVM achieves high F1-score(88.43%)and accuracy(93.60%)for wheat stripe rust disease classification.

Development and Test of Hydrostatic Extraction Scheme in Spectral Model

The introduction of 'hydrostatic extraction' scheme, or 'standard stratification approximation', into spectral model gained some advantages compared with commonly used schemes. However, computational instability may occur for high vertical resolution versions if the stratification parameter C0 taken as a constant. In this paper, the possible cause leading to the instability is discussed and an improved scheme presented where C0 is generalized to be a function of both height and latitudes. Hence the reference atmosphere gets closer to the real atmosphere and the temperature deviation field to be expanded becomes smoother everywhere. Test by real case forecasts shows good computational stability of the new scheme and better prediction performance than-usual schemes of spectral model.

2D-HIDDEN MARKOV MODEL FEATURE EXTRACTION STRATEGY OF ROTATING MACHINERY FAULT DIAGNOSIS

A new feature extraction method based on 2D-hidden Markov model（HMM） is proposed. Meanwhile the time index and frequency index are introduced to represent the new features. The new feature extraction strategy is tested by the experimental data that collected from Bently rotor experiment system. The results show that this methodology is very effective to extract the feature of vibration signals in the rotor speed-up course and can be extended to other non-stationary signal analysis fields in the future.

THE EXTRACTION EQUILIBRIUM MODEL AND SIMULATION OF COUNTERCURRENT SOLVENT EXTRACTION OF Gd-Tb-Dy-HCl-HEH(EHP)-KEROSENE SYSTEM

The extraction equilibrium mathematic models for gadolinium,terbium and dysprosium in HCl-1.5 mol/L HEH(EHP)system covering a relatively wide range of lanthanide concentration and acidity,have been developed.There are four independent variables and nine parameters.The average relative error is 4.56%.A computer program for the simulation of the counter current solvent extraetion process has also been written.Thus,the Gd,Tb and Dy concentrations in both aqueous and organic phase in eaeh stage as well as the aqueous acidity may be calculated.Product purities,distribution ratio and extraction factors may also be obtained thereby.The simulation results so obtained may serve as the referenee data for designing solvent ex- traction processes including those processes providing apart from the conventional outgoing organic stream, outgoing raffinate and an extra outgoing third exit stream either organic or aqueous.

An Impact of Hydrostatic Extraction Scheme on BMRC's Global Spectral Model

There are two important features in geophysical fluid dynamics. One is that the atmospheric and oceanic equations of motion include the Coriolis force; another is that they describe a stratified fluid. The hydrostatic extraction scheme, or standard stratification approximation, posed by Zeng (1979), reflects the second aspect of geophysical fluid dynamics. There exist two major advantages in this scheme; accurate computation of the pressure gradient force can be obtained over steep mountain slopes, and the accumulation error in vertical finite differencing can be reduced, especially near the tropopause.Chen et al (1987) introduced the hydrostatic extraction scheme into a global spectral model, which attained preliminary success at low resolution. Zhang and Sheng et al (1990) developed and improved the hydrostatic extraction scheme in a global spectral model, in which C0, the parameter that represents the stratification of the reference atmosphere, changes not only with height, but also with latitude. The scheme has been incorporated BMRC's global spectral model (IAPB). Four 5-day forecasts have been performed to test the IAPB with the hydrostatic extraction scheme. Objective verifications demonstrate a positive effect of the hydrostatic extration scheme on BMRC's model, particularly at upper levels, over the tropics and the Antartic region.

A novel physical parameter extraction approach for Schottky diodes

Parameter extraction is an important step for circuit simulation methods that are based on physical models of semiconductor devices. A novel physical parameter extraction approach for Schottky diodes is proposed in this paper. By employing a set of analytical formulas, this approach extracts all of the necessary physical parameters of the diode chip in a unique way. It then extracts the package parasitic parameters with a curve-fitting method. To validate the proposed approach, a model HSMS-282 c commercial Schottky diode is taken as an example. Its physical parameters are extracted and used to simulate the diode＇s electrical characteristics. The simulated results based on the extracted parameters are compared with the measurements and a good agreement is obtained, which verifies the feasibility and accuracy of the proposed approach.

Analysis of Response Surface in the Study of RE(NO_3)_3-HNO_3-P507-Kerosene Extraction System

RE(NO_3)_3-HNO_3-P507-kerosene extraction system(RE=La,Ce,Pr,Nd,Sm,Eu,Gd,Tb,Dy,Ho,Er, Tm,Yb,Lu,Y)was studied by the response surface technique.14 models for extracting single rare earth ele- ment in a broad range of acidity and initial rare earth concentration were obtained by using the stepwise regression method.Three-dimensional display of the response surface of the model of extracting Er^(3+)was showed as an example,which reveals clearly the dependence of distribution ratio upon both initial acidity and ini- tial rare earth concentration.

Determination of the Bioaccessibility of Cadmium in Golden Thread by Physiologically Based Extraction Test Digestion Using the in vitro/Caco2 Cell Model and Subsequent Risk Assessment

Background:The ingestion of golden thread contaminated with heavy metals through the food chain leads to detrimental effects to human health.During digestion,not all of the heavy metals could be released to the gastrointestinal tract and readily to be absorbed by human body.Thus,bioaccessibility is an important issue in health risk assessments.Aims and Objectives:The aims and objectives of this study were to investigate the bioaccessibility of Cd in golden thread and assess the associated health risks based on the exposure to bioaccessible Cd.Materials and Methods:Inductively coupled plasma mass spectrometry(ICP-MS)has been applied to determine the Cd content in golden thread.Physiologically based extraction test(PBET)digestion was performed in the in vitro/Caco2 cell model to investigate the bioaccessibility of Cd in golden thread.Furthermore,the target hazard quotient(THQ)was used to assess the risks of the total and the bioaccessible content of Cd in golden thread.Results:The results revealed that the total Cd content in six batches of golden thread ranged from 3.203 to 5.723 mg/kg.After uptake by Caco2 cells,the bioaccessibility of Cd ranged from 42.36%to 59.73%.The results of the risk assessment indicated that prior to uptake by Caco2 cells,the THQ values of Cd for all batches of golden thread were greater than 1.However,after uptake by Caco2 cells,the THQ values of Cd in all samples were less than 1,thus suggesting that the risks were at a safe level.Conclusion:This study was the first to perform health risk assessment with bioaccessible heavy metals present in traditional Chinese medicine by PBET digestion using an in vitro/Caco2 cell model,thus enabling us to obtain more accurate and objective results while allowing us to avoid unnecessary government intervention and to establish more reasonable limit standards for heavy metals.

Small-signal model parameter extraction for AlGaN/GaN HEMT

A new 22-element small signal equivalent circuit model for the AlGaN/G N high electron mobility transistor（HEMT） is presented. Compared with the traditional equivalent circuit model, the gate forward and breakdown conductions（G_（gsf） and G_（gdf）） are introduced into the new model to characterize the gate leakage current. Additionally, for the new gate-connected field plate and the source-connected field plate of the device, an improved method for extracting the parasitic capacitances is proposed, which can be applied to the small-signal extraction for an asymmetric device. To verify the model, S-parameters are obtained from the modeling and measurements. The good agreement between the measured and the simulated results indicate that this model is accurate,stable and comparatively clear in physical significance.

Temperature-variable high-frequency dynamic modeling of PIN diode

The PIN diode model for high frequency dynamic transient characteristic simulation is important in conducted EMI analysis. The model should take junction temperature into consideration since equipment usually works at a wide range of temperature. In this paper, a temperature-variable high frequency dynamic model for the PIN diode is built, which is based on the Laplace-transform analytical model at constant temperature. The relationship between model parameters and temperature is expressed as temperature functions by analyzing the physical principle of these parameters. A fast recovery power diode MUR1560 is chosen as the test sample and its dynamic performance is tested under inductive load by a temperature chamber experiment, which is used for model parameter extraction and model verification. Results show that the model proposed in this paper is accurate for reverse recovery simulation with relatively small errors at the temperature range from 25 to 120 ℃.

An Intelligent Heuristic Manta-Ray Foraging Optimization and Adaptive Extreme Learning Machine for Hand Gesture Image Recognition

The development of hand gesture recognition systems has gained more attention in recent days,due to its support of modern human-computer interfaces.Moreover,sign language recognition is mainly developed for enabling communication between deaf and dumb people.In conventional works,various image processing techniques like segmentation,optimization,and classification are deployed for hand gesture recognition.Still,it limits the major problems of inefficient handling of large dimensional datasets and requires more time consumption,increased false positives,error rate,and misclassification outputs.Hence,this research work intends to develop an efficient hand gesture image recognition system by using advanced image processing techniques.During image segmentation,skin color detection and morphological operations are performed for accurately segmenting the hand gesture portion.Then,the Heuristic Manta-ray Foraging Optimization(HMFO)technique is employed for optimally selecting the features by computing the best fitness value.Moreover,the reduced dimensionality of features helps to increase the accuracy of classification with a reduced error rate.Finally,an Adaptive Extreme Learning Machine(AELM)based classification technique is employed for predicting the recognition output.During results validation,various evaluation measures have been used to compare the proposed model’s performance with other classification approaches.