ESSENTIAL RELATIONSHIP BETWEEN DOMAIN-BASED ONE-CLASS CLASSIFIERS AND DENSITY ESTIMATION

One-class support vector machine （OCSVM） and support vector data description （SVDD） are two main domain-based one-class （kernel） classifiers. To reveal their relationship with density estimation in the case of the Gaussian kernel, OCSVM and SVDD are firstly unified into the framework of kernel density estimation, and the essential relationship between them is explicitly revealed. Then the result proves that the density estimation induced by OCSVM or SVDD is in agreement with the true density. Meanwhile, it can also reduce the integrated squared error （ISE）. Finally, experiments on several simulated datasets verify the revealed relationships.

Coherence estimation algorithm using Kendall's concordance measurement on seismic data

The coherence method is always used to describe the discontinuity and heterogeneity of seismic data. In traditional coherence methods, a linear correlation coefficient is always used to measure the relationship between two random variables （i.e., between two seismic traces）. However, mathematically speaking, a linear correlation coefficient cannot be applied to describe nonlinear relationships between variables. In order to overcome this limitation of liner correlation coefficient. We proposed an improved concordance measurement algorithm based on Kendall＇s tau. That mainly concern the sensitivity of the liner correlation coefficient and concordance measurements on the waveform. Using two designed numerical models tests sensitivity of waveform similarity affected by these two factors. The analysis of both the numerical model results and real seismic data processing suggest that the proposed method, combining information divergence measurement, can not only precisely characterize the variations of waveform and the heterogeneity of an underground geological body, but also does so with high resolution. In addition, we verified its effectiveness by the actual application of real seismic data from the north of China.

Monthly variation in the fat content of anchovy (Engraulis japonicus) in the Yellow Sea: implications for acoustic abundance estimation

Anchovy is a key species in the Yellow Sea ecosystem. An accurate estimate of anchovy abundance is vital for the management of the anchovy stock and measurement of the ecosystem response to changes in anchovy abundance. However, the acoustic fish abundance estimate may be biased by 30%-40% if the fat-content induced target strength variation is not taken into account. We measured the monthly variation in the fat content of anchovy (Engraulis japonicus) in the Yellow Sea, and evaluated the potential effect of variation in fat content on the acoustic assessment of anchovy abundance. The fat content of anchovy varied seasonally, with two maxima and two minima in a year. The highest fat content (14.75%) was measured in the pre-spawning period in May, and the lowest fat content (2.48%) was measured during the post-spawning period in October. Fat content appeared to correlate with water content, but not body size. Assuming that the target strength is decreased by 0.2dB for every 1% increase in fat content, the seasonal difference in the target strength of anchovy may be as high as 2.45 dB. Given this, the acoustic abundance estimate may be biased by between 43% and 76%. Our results highlight the need for more information on the changes in fat content of fishes whose abundance is estimated by acoustic surveys.

Emotional Vector Distance Based Sentiment Analysis of Wakamono Kotoba

In this paper,we propose a method for estimating emotion in Wakamono Kotoba that were not registered in the system,by using Wakamono Kotoba example sentences as features.The proposed method applies Earth Mover's Distance(EMD) to vector of words.As a result of the evaluation experiment using 14 440 sentences,higher estimation accuracy is obtained by considering emotional distance between words-an approach that had not been used in the conventional research-than by using only word importance value.

NOVEL SENSORLESS VECTOR CONTROL SYSTEM OF INDUCTION MACHINE BASED ON FLUX OBSERVER IN FIELD WEAKENING

A speed-sensorless vector control system for induction machines （IMs）is presented, According to the vector control theory of IMs, the rotor flux is estimated based on a flux observer,and the speed is estimated through the method of q-axis rotor flux converging on zero with proportional integral regulator, A 0.75 kW,50 Hz,two-pole induction machine was used in the simulation and experimental verification, The simulation model was constructed in Matlab. A series of tests were performed in the field weakening region, for both no-load and loaded operation. The estimated speed tracks the actual speed well in the based speed region and field weakening region （ 1 per unit value to 4 per unit value）. The small estimation error of residual speed is due to the existence of slip.

SVM for density estimation and application to medical image segmentation

A method of medical image segmentation based on support vector machine (SVM) for density estimation is presented. We used this estimator to construct a prior model of the image intensity and curvature profile of the structure from training images. When segmenting a novel image similar to the training images, the technique of narrow level set method is used. The higher dimensional surface evolution metric is defined by the prior model instead of by energy minimization function. This method offers several advantages. First, SVM for density estimation is consistent and its solution is sparse. Second, compared to the traditional level set methods, this method incorporates shape information on the object to be segmented into the segmentation process. Segmentation results are demonstrated on synthetic images, MR images and ultrasonic images.

Micromixing Efficiency of Viscous Media in Micro-channel Reactor

Micromixing efficiency of viscous media in Y-type micro-channel reactor was studied by using iodide-iodate test reaction as working system.Experiments were carried out in water-glycerin mixtures with 7 different viscosities.The experimental results showed that segregation index of the micro-channel reactor increases with the decrease of volumetric flow rate and the increase of solution viscosity.Based on the incorporation model,the micromixing time tm of the micro-channel reactor was estimated in the range of 10-4-10-3s at different viscosities,which indicated that the micro-channel reactor possesses a much better micromixing performance compared to the stirred tank(tm=0.02-0.2s).

Estimation of the Total Dust Column and Dry Deposition Flux over the Yellow Sea,China Based on Shipboard Sun Photometer Measurements:Case Study

The total dust column and the dry deposition flux were calculated based on the optical properties that were measured by a shipboard sun photometer POM-01 MK II in a cloud-free and nonfrontal dust condition on 24 April 2006. The total dust column was calculated by using an integration method of the particle size distribution; the mean value was 1.42±0.30 g m 2. A linear correlation between the total dust column and the aerosol optical depth （AOD） with a linear factor of 2.7 g m 2 over the Sahara was applied to calculate the total dust column in this study; the results were lower than these calculated by the integration method. A reasonable factor of 3.2 g m^-2 was achieved by minimizing the standard deviation （SD） of the two methods. The two layers model, which includes the deposition processes of turbulent transfer, Brownian diffusion, impaction and gravitational settling over the sea＇s surface, was used to calculate the dry deposition flux; the mean value was 5.05±2.49 μg m^-2 s^-1. A correlation among the total dust column, dry deposition flux, AOD, and effective radius was discussed. The correlation between the total better than that between dust column and the AOD was the total dust column and the effective radius; however, the correlation between the dry deposition flux and the effective radius was better than that between the dry deposition flux and the AOD.

The Sorption Isosteric Heats of Rough Rice in China

Equilibrium moisture content （EMC） data for rough rice of thirteen Chinese varieties were obtained by static gravimetric method at five different temperatures （10, 20, 25, 30, and 35 ℃） and 11% to 96% equilibrium relative humidity （ERH）. Six models, i.e., Brunauer-Emmett-Teller, Guggenheim-Anderson-deBoer, Modified Chung-Pfost （MCPE）, Modified Henderson, Modified Oswin, and Strohman-Yoerger （STYE） fitted the EMC/ERH data based on the coefficient of determination, residue sum-of-squares, standard error of estimate, and mean relative percent error. The best fitted equations were MCPE and STYE, but MCPE is three-parameter, readily transformed equation and adopted in this study. The isosteric heats for both rough rice desorption and adsorption, and for both the sorption of Japonica and Indica rice, decreased rapidly with an increase in seed moisture content （m.c.） until the m.c. of 20% dry basis （d.b.） reached, and thereafter they decreased smoothly with increasing moisture content. The isosteric heats of rough rice desorption were higher than those of adsorption below the m.c. of 22.5% d.b., but thereafter, there was no significant difference found between desorption and adsorption. The sorption isosteric heats of Indica rice were slightly higher than those of Japonica rice under all moisture contents at a constant temperature. These results provide a sound basis for future work on the drying and storage of rice.

A complexity-scalable software-based MPEG-2 video encoder

With the development of general-purpose processors (GPP) and video signal processing algorithms, it is possible to implement a software-based real-time video encoder on GPP, and its low cost and easy upgrade attract developers' interests to transfer video encoding from specialized hardware to more flexible software. In this paper, the encoding structure is set up first to support complexity scalability; then a lot of high performance algorithms are used on the key time-consuming modules in coding process; finally, at programming level, processor characteristics are considered to improve data access efficiency and processing parallelism. Other programming methods such as lookup table are adopted to reduce the computational complexity. Simulation results showed that these ideas could not only improve the global performance of video coding, but also provide great flexibility in complexity regulation.

Monitoring Media Velocity Variations with Coda Wave Interferometry

Multiply scattered waves are sensitive to media changes owing to the effect of repeated sampling,superposition and amplification. Based on this characteristic,small-medium changes could be detected by using coda wave interferometry. In recent years,coda wave interferometry has been widely used in estimating velocity variation with high precision in areas such as seismology and non-destructive testing. This paper systematically presents the principle and research status of coda wave interferometry,and especial focus is placed on the research of media velocity variations by using repeating earthquakes,artificial sources,and ambient noise. Applications of coda wave interferometry can contribute to the more subtle understanding of dynamic evolution process in the medium.

A new compensation method for angular rate estimation of non-gyro inertial measurement unit

A new compensation method for angular rate estimation of non-gyro inertial measurement unit （NGIMU） is proposed in terms of the existence of aecelerometer mounting error, which seriously affects the precision of navigation parameter estimation. Using the accelerometer output error function, the algorithm compensates the posture parameters in the traditional algorithm of angular rate estimation to reduce the accelerometer mounting error. According to the traditional aceelerometer configurations, a novel nine-accelerometer confi-guration of NGIMU is presented with its mathematic model constructed. The semi-hardware simulations of the proposed algorithm are investigated based on the presented NGIMU configuration, and the results show the effectivity of the new algorithm.

Asymptotic Formulas for Thermography Based Recovery of Anomalies

We start from a realistic half space then use to develop a mathematical asymptotic model for thermal imaging, which we analysis well suited for the design of reconstruction algorithms. We seek to reconstruct thermal anomalies only through their rough features. With this way our proposed algorithms are stable against measurement noise and geometry perturbations. Based on rigorous asymptotic estimates, we first obtain an approximation for the temperature profile which we then use to design noniterative detection algorithms. We show on numerical simulations evidence that they are accurate and robust. Moreover, we provide a mathematical model for ultrasonic temperature imaging, which is an important technique in cancerous tissue ablation therapy.

Variable Selection Procedures in Linear Regression Models with Screening Consistency Property

There are two fundamental goals in statistical learning： identifying relevant predictors and ensuring high prediction accuracy. The first goal, by means of variable selection, is of particular importance when the true underlying model has a sparse representation. Discovering relevant predictors can enhance the performance of the prediction for the fitted model. Usually an estimate is considered desirable if it is consistent in terms of both coefficient estimate and variable selection. Hence, before we try to estimate the regression coefficients β , it is preferable that we have a set of useful predictors m hand. The emphasis of our task in this paper is to propose a method, in the aim of identifying relevant predictors to ensure screening consistency in variable selection. The primary interest is on Orthogonal Matching Pursuit（OMP）.

Estimation of Fat-tail Weight by External Fat-tail Dimensions in Lori-Bakhtiari Sheep

In this study fat-tail weight was estimated by external fat-tail dimensions. External fat-tail dimensions included upper, middle and lower width, length, length of gap, depth, upper and middle circumference recorded on 1,482 head of Lori-Bakhtiari lambs at 6 months. Of these about 311 lambs were slaughtered at the age of six months. Prediction equations were derived for fat-tail weight by multiple regression analyses with two methods. The results showed that the measure of middle circumference fat-tail was as most important measure in estimation of fat-tail weight. The measure of middle circumference fat-tail accounted for 76 percent of variation in fat-tail weight. The regression equations for predicting fat-tail weight using external fat-tail dimensions obtained from stepwise regression procedure can be estimated only with using from the lower width, length, middle circumference fat-tail and body weight with high acc, uracy （0.92）. Average of fat-tail weight estimated in the age of six months in lambs was 2.39 kg. The highest regression coefficient of external fat-tail dimensions on fat-tail weight observed for the length of fat-tail （0.095 kg）. Results of the present investigation showed that fat-tail weight in live sheep of Lori-Bakhtiari, could be estimated by measuring external fat-tail dimensions.

低光泽度印刷色谱色貌数据组的建立与评价

色貌预测是现代颜色科学领域的基本理论和技术。为了评价低光泽度彩色印刷色谱的色貌,以丽印胶版纸印制的彩色印刷色谱为研究对象,根据颜色科学和心理物理学相关实验,建立其色貌参数样本数据组。采用相对系数R2和差异系数CV等数理统计方法,评价这种印刷色谱中Y-M内页在三种不同的照明光源下色貌的视觉评估结果。实验数据分析表明,在D65、A和TL84三种光源中,人眼在A光源下对颜色的识别能力明显不同于D65和TL84光源;同样在这三种光源中人眼对明度和色调的评估准确度最高,彩度最差。

Modeling tree root diameter and biomass by ground-penetrating radar

Roots play a key role in ecosystem functioning as they transfer water and nutrients from soil to plants. Traditional methods for measuring roots are labor-intensive and destructive in nature, which limits quantitative and repeatable assessments in long- term research. Ground-penetrating radar （GPR） provides a non-destructive method to measure plant roots. Based on the superiority of GPR with 2 GHz frequency, we developed a new, practical method to estimate root biomass. First, average root matter density was measured by collecting a small number of root samples. Second, under controlled, experimental conditions in a sandy area, a root diameter estimation model base on GPR was developed from which root diameter was estimated. Third, root volume was calculated using the estimated root diameter and assuming the shape of roots to be cylindrical. Finally, root biomass was estimated by averaging root matter density and root volume. Results of this study suggest the following： （1） the density of coarse roots with diameters greater than 0.5 cm is relatively uniform; （2） a new wave shape parameter, AT, extracted from profile data of 2 GHz frequency antenna is independent of root depth, thus enabling the construction of a root diameter estimation model with high accuracy; and （3） results of a field experiment demonstrated the GPR-based method to be feasible and effective in estimating biomass of coarse roots. These findings are helpful for improving GPR-based root diameter and biomass estimation models and suggest the potential of GPR data in studying root systems.

On the Bergman representative coordinates

We study the set where the so-called Bergman representative coordinates (or Bergman functions) form an immersion. We provide an estimate of the size of a maximal geodesic ball with respect to the Bergman metric contained in this set. By concrete examples we show that these estimates are the best possible.

Estimation on Geometric Measure of Quantum Coherence

We study the geometric measure of quantum coherence recently proposed in [Phys. Rev. Lett. 115(2015)020403]. Both lower and upper bounds of this measure are provided. These bounds are shown to be tight for a class of important coherent states—maximally coherent mixed states. The trade-off relation between quantum coherence and mixedness for this measure is also discussed.

Estimation on structural responses using multi scale measurements

Different measurands from the different types of sensors can obtain different information regarding the structural behavior in a real structural health monitoring system.To enrich information and estimate the structural responses based on much more known information,the estimation on structural responses using multi scale measurements from multi-type sensors is proposed in this paper.Pattern identification is constructed with the pattern library given by strain measurements and deformation measurements.Considering the uncertainty of the measurements as well as to enhance the robustness of the proposed algorithm,more than one best pattern is selected to synthesize the finally estimated stress responses.To validate the capacity of the proposed acquisition method using multi scale measurements,finite element model analysis is conducted to estimate the structural stress response in Shenzhen Bay Stadium as an example.The performance of the pattern identifications,constructed by two kinds of pattern libraries captured by sole strain measurement,and multi scale measurements which are constructed by both kinds of strain measurements and deformation measurements,respectively,are compared in this paper to observe measurements constructed from strain measurements and deformation measurements outperformed others.Errors analysis for a series of parametric studies in which noise at different levels has also included in the measurements are further carried out,and robustness of the proposed information acquisition scheme under noisy measurement is demonstrated.