Advance of Rice Recognition and Monitoring by SAR

Synthetic Aperture Radar（SAR） is a more effective remote sensing data source for rice recognition and monitoring than optical remote sensing in the regions with more wet and cloudy sky due to its all-weather, all-time, high resolution and wide covering characteristics. This paper summarizes SAR types and their feature used for rice study, introduces the backscattering model for rice monitoring, and analyses the main factors influencing backscattering coefficient. The studies of rice recognition and monitoring based on SAR in domestic and abroad are reviewed and the futures in the related areas are prospected.

OPTIMIZATION OF WEIGHTED HIGH-RESOLUTION RANGE PROFILE FOR RADAR TARGET RECOGNITION

For the recognition of high-resolution range profile （HRRP） in radar, the weighted HRRP can reduce the instability of range cells caused by the attitude change of targets. A novel approach is proposed to optimize the weighted HRRP. In the approach, the separability of weighted HRRPs in different targets is measured by de- signing an objective function, and the weighted coefficients are computed by using the gradient descent method, thus enhancing the influence of stable range cells. Simulation results based on five aircraft models show that the approach can effectively optimize the weighted HRRP and improve the recognition accuracy.

An automatic seismic signal detection method based on fourth-order statistics and applications

Real-time, automatic, and accurate determination of seismic signals is critical for rapid earthquake reporting and early warning. In this study, we present a correction trigger function（CTF） for automatically detecting regional seismic events and a fourth-order statistics algorithm with the Akaike information criterion（AIC） for determining the direct wave phase, based on the differences, or changes, in energy, frequency, and amplitude of the direct P- or S-waves signal and noise. Simulations suggest for that the proposed fourth-order statistics result in high resolution even for weak signal and noise variations at different amplitude, frequency, and polarization characteristics. To improve the precision of establishing the S-waves onset, first a specific segment of P-wave seismograms is selected and the polarization characteristics of the data are obtained. Second, the S-wave seismograms that contained the specific segment of P-wave seismograms are analyzed by S-wave polarization filtering. Finally, the S-wave phase onset times are estimated. The proposed algorithm was used to analyze regional earthquake data from the Shandong Seismic Network. The results suggest that compared with conventional methods, the proposed algorithm greatly decreased false and missed earthquake triggers, and improved the detection precision of direct P- and S-wave phases.

Multi-SPline Technique for the Extraction of Drag Coeffidents from Radar Data

In the preparation of firing tables, the determination of projectile drag coefficientsthrough firing test radar data reduction is very important. Many methods have been developed for this work but none of them appear to be satisfactory in one Way or another. Inthis paper a multi-spline model of drag coefficient (cd) curve is developed that can guaranteefirst derivative continuity of the cd curve and has good flexibility of fitting accurately to acd curve from subsonic up to supersonic range. Practical firing data reduction tests showboth fast convergence and accurate fitting results. Typical velocity fitting RMS errors are0.05-0.08 m/s.

Radar Target Discrimination based on waveletPackets for Reduced data Storage

In order to storage resource of a radar recognition system, schemes for reducing data storage and for correlation discrimination of radar based on wavelet packets were proposed Experiment results at various signal-to-noise ratios were given The given.ability of the reduced data method's validity are supported by experimental results. Using optimal basis can get higher successful recognition rate using rigid wavelet basis.

SAR IMAGE RECOGNITION BASED ON MULTI-ASPECT OF SHADOW INFORMATION

The traditional synthetic aperture radar（SAR） image recognition techniques focus on the electro magnetic （EM） scattering centers, ignoring the important role of the shadow information on the SAR image recognition. It is difficult to classify targets by the shadow information independently, because the shadow shape is dependent on the radar aspect angle, the depression angle and the resolution. Moreover, the shadow shapes of different targets are similar. When the multiple SAR images of one target from different aspects are available, the performance of the target recognition can be improved. Aimed at the problem, a multi-aspect SAR image recognition technique based on the shadow information is developed. It extracts shadow profiles from SAR images, and takes chain codes as the feature vectors of targets. Then, feature vectors on multiple aspects of the same target are combined with feature sequences, and the hidden Markov model （HMM） is applied to the feature sequences for the target recognition. The simulation result shows the effectiveness of the method.

Cloning and expression analysis of a long type peptidoglycan recognition protein(PGRP-L) from Xenopus tropicalis

Peptidoglycan recognition proteins（PGRPs） are a family of pattern recognition receptors（PRRs） of the immune system,which bind and hydrolyze bacterial peptidoglycan.Here,a long type PGRP（PGRP-L） was first cloned in the lower vertebrate species Xenopus tropicalis（Xt）.The XtPGRP-L possessed a conserved genomic structure with five exons and four introns.The alignment and phylogenetic analysis indicated that XtPGRP-L might be a type of amidase-like PGRP.The 3-D model showed that XtPGRP-L possessed a conserved structure compared with the Drosophila PGRP-Lb.During embryonic development,XtPGRP-L was not expressed until the 72 h tadpole stage.In adult tissues,it was strongly expressed in the liver,lung,intestine,and stomach.Furthermore,after LPS stimulation,the expression of XtPGRP-L was up-regulated significantly in the liver,intestine and spleen,indicating that XtPGRP-L may play an important role in the innate immunity of Xenopus tropicalis.

Construction and realization of the knowledge base and inference engine of an IDSS model for air-conditioning cooling/heating sources selection

The knowledge representation mode and inference control strategy were analyzed according to the specialties of air-conditioning cooling/heating sources selection. The constructing idea and working procedure for knowledge base and inference engine were proposed while the realization technique of the C language was discussed. An intelligent decision support system (IDSS) model based on such knowledge representation and inference mechanism was developed by domain engineers. The model was verified to have a small kernel and powerful capability in list processing and data driving, which was successfully used in the design of a cooling/heating sources system for a large-sized office building.

Generalization Capabilities of Feedforward Neural Networks for Pattern Recognition

This paper studies the generalization capability of feedforward neural networks (FNN).The mechanism of FNNs for classification is investigated from the geometric and probabilistic viewpoints. It is pointed out that the outputs of the output layer in the FNNs for classification correspond to the estimates of posteriori probability of the input pattern samples with desired outputs 1 or 0. The theorem for the generalized kernel function in the radial basis function networks (RBFN) is given. For an 2-layer perceptron network (2-LPN). an idea of using extended samples to improve generalization capability is proposed. Finally. the experimental results of radar target classification are given to verify the generaliztion capability of the RBFNs.

NON-UNIFORM LINEAR ARRAY CONFIGURATION FOR MIMO RADAR

Array configuration of multiple-input multiple-output （MIMO） radar with non-uniform linear array （NLA） is proposed. Unlike a standard phased-array radar where NLA is used to generate thinner beam patterns, in MIMO radar the property of NLA is exploited to get more distinct virtual array elements so as to improve pa- rameter identifiability, which means the maximum number of targets that can be uniquely identified by the radar. A class of NLA called minimum redundancy linear array （MRLA） is employed and a new method to construct large MRLAs is descrihed. The numerical results verify that compared to uniform linear array （ULA） MIMO radars, NLA MIMO radars can retain the same parameter identifiability with fewer physical antennas and achieve larger aperture length and lower Cramer-Rao bound with the same number of the physical antennas.

Expression and identification of recombinant soluble single-chain variable fragment of monoclonal antibody MC3

AIM: To generate soluble single chain variable fragments (ScFv) of monoclonal antibody MC3 recognizing colorectal and gastric carcinomas. METHODS: mRNA was isolated from the hybridoma cell line producing MC3 and the DNAs encoding variable domains of heavy and light chains (VH and VL) of the antibody were amplified separately by RT-PCR and assembled into ScFv DNA with a linker DNA. The ScFv DNA was ligated into the phagemid vector pCANTAB5E and the ligated sample was transformed into E.coli TG1.The transformed cells were infected with M13KO7 helper phage to yield recombinant phages. After two rounds of panning with gastric carcinoma cell line AGS highly expressing MC3-binding antigen, the phage clones displaying ScFv fragments of the antibody were selected by ELISA. 4 phage clones showing strong signal in ELISA were used to infect E.coli HB2151 to express soluble ScFvs. The soluble ScFvs were identified by Dot blot and Western blot, and their antigen-binding activity was assayed by ELISA. The VH and VL DNAs of the ScFv DNA derived from phage clone 19 were sequenced. RESULTS: The VH,VL and ScFv DNAs were about 340 bp, 320 bp and 750 bp respectively. After two rounds of panning to the recombinant phages, 18 antigen-positive phage clones were selected from 30 preselected phage clones by ELISA. All the soluble ScFvs derived from the 4 out of the 18 antigen-positive phage clones were about M(r)32000 and concentrated in periplasmatic space under the given culture condition. The soluble ScFvs could bind the antigen, and they shared the same binding site with MC3. The sequences of the VH and VL DNAs of the MC3 ScFv showed that the variable antibody genes belonged to the IgG1 subgroup,kappa-type. CONCLUSION: The soluble ScFv of MC3 is successfully produced, which not only provides a possible novel targeting vehicle for in vivo and in vitro study on associated cancers, but also offers the antibody a stable genetic source.

An Algorithm to Construct Concurrent Reachability Graph of Petri Nets

Reachability graph is a very important tool to analyze the dynamic properties of Petri nets, but the concurrent relation of transitions in Petri nets cannot be represented by reachability graph. Petri net is a concurrent system, while reachability graph is a serial one. However, concurrency is a kind of property which is not only very significant but also difficult to be analyzed and controlled. This paper presents the concepts of concurrent reachable marking and concurrent reachable graph in order to represent and analyze the concurrent system. The algorithm constructing concurrent reachable marking set and concurrent reachability graph is also shown so that we can study the response problems among services in a network computing environment and analyze the throughput of the system. The Dining Philosophers Problem, which is a classic problem of describing the management of concurrent resources, is given as an example to illustrate the significance of concurrent reachability graph.

IMAGE-BASED SCALING FOR SHIP TOP VIEW ISAR IMAGES

A high quality top view or side view ship ISAR image with proper cross-range scale is very useful for target recognition. A technique aiming at solving the ship top view image scaling is developed, in which the cross-range scale information is obtained by measuring the slopes of the two feature lines of the ship, the centerline and the stern line. Neither the prior knowledge about the ship nor the tracking data is required. The proposed technique is fully based on the image. It is used with ease and high efficiency. Examples are provided to demonstrate its effectiveness with both simulated and real data. The scaled results are in accordance with the real shape of the ship.

A WEIGHTED FEATURE REDUCTION METHOD FOR POWER SPECTRA OF RADAR HRRPS

Feature reduction is a key process in pattern recognition. This paper deals with the feature reduction methods for a time-shift invariant feature, power spectrum, in Radar Automatic Target Recognition (RATR) using High-Resolution Range Profiles (HRRPs). Several existing feature reduction methods in pattern recognition are analyzed, and a weighted feature reduction method based on Fisher's Discriminant Ratio (FDR) is proposed in this paper. According to the characteristics of radar HRRP target recognition, this proposed method searches the optimal weight vector for power spectra of HRRPs by means of an iterative algorithm, and thus reduces feature dimensionality. Compared with the method of using raw power spectra and some existing feature reduction methods, the weighted feature reduction method can not only reduce feature dimensionality, but also improve recognition performance with low computation complexity. In the recognition experiments based on measured data, the proposed method is robust to different test data and achieves good recognition results.

Research on Radar Emitter Attribute Recognition Method

In order to solve emitter recognition problems in a practical reconnaissance environment, attribute mathematics is introduced. The basic concepts and theory of attribute set and attribute measure are described i n detail. A new attribute recognition method based on attribute measure is prese nted in this paper. Application example is given, which demonstrates this new me thod is accurate and effective. Moreover, computer simulation for recognizing th e emitter purpose is selected, and compared with classical statistical pattern r ecognition through simulation. The excellent experimental results demonstrate t hat this is a brand-new attribute recognition method as compared to existing st atistical pattern recognition techniques.

Target polarization recognition under rain and snow cluster

This paper derives the polarization scattering matrix of both the warship target and the interferential chaff conditioned on the exit of rain and snow cluster,and furthermore,proposes a method to recognize the chaff and warship by analyzing their corresponding polarization information.This method mainly aims to the radar,which can receive both the left and right circularly polarized wave to catch the full polarization information of echoes,and then acquires more accurate polarization characteristics of the target and chaff after getting rid of the impacts of rain and snow cluster from the polarization scattering power matrix of echoes.In order to further improve the recognition probability,the non-linear polarization transformation is introduced to make the separation of target and chaff more realizable.It indicates that the resulting performance is incredible for the traditional recognition in time and frequency domain.

An analog front-end circuit for ISO/IEC 15693-compatible RFID transponder IC

The 13.56 MHz analog front-end circuit for ISO/IEC 15693-compatible radio frequency identification (RFID) trans- ponder IC presented in this paper converts RF power to DC and extracts clock and data from the interrogator by 10% or 100% ASK modulation. The transponder sends data back to the interrogator by load modulation technology. The electrostatic discharge (ESD) protection circuits function to limit RF voltage to a safe level. An inductive coupling simulation modelling for 13.56 MHz RFID system is presented, with simulation results showing that the transponder operates over a wide range of electromagnetic field strength from Hmin (150 mA/m) to Hmax (5 A/m). The transponder IC is implemented in SMIC 0.35-μm three-metal two-poly mixed signal CMOS technology with embedded EEPROM.

Towards a Formalized Ontology-Based Requirements Model

The goal of this paper is to take a further step towards an ontological approach for representing requirements information. The motivation for ontologies was discussed. The definitions of ontology and requirements ontology were given. Then, it presented a collection of informal terms, including four subject areas. It also discussed the formalization process of ontology. The underlying meta-ontology was determined, and the formalized requirements ontology was analyzed. This formal ontology is built to serve as a basis for requirements model. Finally, the implementation of software system was given.

Mining Knowledge from Result Comparison Between Spatial Clustering Themes

This paper introduces some definitions and defines a set of calculating indexes to facilitate the research, and then presents an algorithm to complete the spatial clustering result comparison between different clustering themes. The research shows that some valuable spatial correlation patterns can be further found from the clustering result comparison with multi-themes, based on traditional spatial clustering as the first step. Those patterns can tell us what relations those themes have, and thus will help us have a deeper understanding of the studied spatial entities. An example is also given to demonstrate the principle and process of the method.

AUTOMATIC TARGET RECOGNITION OF RADAR HRRP BASED ON HIGH ORDER CENTRAL MOMENTS FEATURES

The paper addresses the problem of target recognition using High-resolution Radar Range Profiles(HRRP).A novel approach of feature extraction and dimension reduction based on extended high order central moments is proposed in order to reduce the dimension of range profiles.Features extracted from radar HRRPs are normalized and smoothed,and then comparative analysis of the similar approaches is done.The range profiles are obtained by step frequency technique using the two-dimensional backscatters distribution data of four different aircraft models.The template matching method by nearest neighbor rules,which is based on the theory of kernel methods for pattern analysis,is used to classify and identify the range profiles from four different aircrafts.Numerical simulation results show that the proposed approach can achieve good performance of stability,shift independence and higher recognition rate.It is helpful for real-time identification and the engineering implements of automatic target recognition using HRRP.The number of required templates could be reduced con-siderably while maintaining an equivalent recognition rate.