摘要:
Parabolic phase is commonly utilized for concave or convex metalens. Here, we report for the first time using such approach for determinant diffusion of scattering waves in wide incident angles by arranging parabolic-phased subarrays in arbitrary coding sequences. To engineer multi-spectrum polarization-dependent bifunctional scatterings, multi-mode anisotropic meta-atoms are utilized without polarization cross-talking. For verification, two proof-to-concept coding metasurfaces are designed, fabricated and measured at microwave regime. Numerical and experimental results show that the -10 dB backscatter radar cross-section (RCS) reduction is clearly observed in C, X and Ku band. Moreover, the diffusion behavior can be engineered dual-polarized and even bifunctional by integrating vortex scattering. Our findings, free of time-consuming optimizations, opened a rapid, easy but very efficient way for stealth applications under bistatic detection.
摘要:
This study proposed a new hybrid approach for short-term water demand prediction. Raw water demand data were decomposed into a set of intrinsic mode functions (IMFs) component and a residue by using ensemble empirical mode decomposition (EEMD) method. IMF1 is the main random component of the raw water demand data, the continuous deep belief neural network (CDBNN) model is used to predict IMF1. Other IMFs and residue can be recombined employing autoregressive integrated moving average (ARIMA) model for forecasting, this method reduces forecasting steps without increasing the forecasting error. The final forecasting result was obtained by summing the forecasting results of the two models. A historical hourly water demand data from an urban waterworks of Zhuzhou, China were investigated by the hybrid method. Simulation results indicate that the proposed approach has higher forecasting accuracy than back propagation neural network (BPNN), support vector regression (SVR), EEMD and their combinations.
摘要:
Conjugate gradient methods can be used with advantages such as fast convergence and low memory requirement in real applications. A conjugate gradient-based neuro-fuzzy learning algorithm for zero-order Takagi-Sugeno inference systems is proposed in this paper. Compared with the existing gradient-based algorithm, this method enhances the learning performance.
期刊:
Journal of Computational and Applied Mathematics,2018年329:57-67 ISSN:0377-0427
通讯作者:
Zhang, Jie
作者机构:
[Liu, Xiuping; Li, Yujiao; Cao, Junjie; Chen, He] Dalian Univ Technol, Sch Math Sci, Dalian, Peoples R China.;[Cao, Junjie] Nanchang Hangkong Univ, Coll Math & Informat Sci, Nanchang, Jiangxi, Peoples R China.;[Zhang, Jie] Liaoning Normal Univ, Sch Math, Dalian, Peoples R China.;[Zou, Changqing] Hengyang Normal Univ, Hengyang, Hunan, Peoples R China.
通讯机构:
[Zhang, Jie] L;Liaoning Normal Univ, Sch Math, Dalian, Peoples R China.
会议名称:
International Conference on Information and Computational Science (ICICS)
会议时间:
AUG 02-06, 2016
会议地点:
Dalian Univ Technol, Dalian, PAKISTAN
会议主办单位:
Dalian Univ Technol
关键词:
Normal estimation;Point cloud;Neighborhood shift
摘要:
For accurately estimating the normal of a point, the structure of its neighborhood has to be analyzed. All the previous methods use some neighborhood centering at the point, which is prone to be sampled from different surface patches when the point is near sharp features. Then more inaccurate normals or higher computation cost may be unavoidable. To conquer this problem, we present a fast and quality normal estimator based on neighborhood shift. Instead of using the neighborhood centered at the point, we wish to locate a neighborhood containing the point but clear of sharp features, which is usually not centering at the point. Two specific neighborhood shift techniques are designed in view of the complex structure of sharp features and the characteristic of raw point clouds. The experiments show that our method out-performs previous normal estimators in either quality or running time, even in the presence of noise and anisotropic sampling. (C) 2017 Elsevier B.V. All rights reserved.
作者机构:
[Zitun Yang; Wenpei Xiao; Meng Hu; Cheng Peng; Yanxia Chen; Biao Gu] Key Laboratory of Functional Organometallic Materials of College of Hunan Province, College of Chemistry and Materials Science, Hengyang Normal University
摘要:
The increasing Hg2+contamination in environment and ecosystem has gained wide attention and thus demands for its facile and effective detection.In this study,we constructed a novel fluorescent probe(DCM-Hg)for Hg2+detection by incorporating the 1,3-dithiane group to the dicyanomethylene-4H-pyran fluorophore.This probe can selectively detect Hg2+via the Hg2+-triggered deprotection reaction of thioacetals,which results in a distinct color change from purple to pink and significant fluorescent turn-on signal in the near-infrared(NIR)region.The NIR fluorescence intensity increased linearly with Hg2+level in the range of 0~70 μM and the detection limit was found to be 2.4 × 10-8 mol/L.Moreover,the probe could detect Hg2+on paper strips and image Hg2+in living cells,which demonstrates its potential application in environment and biological science.
摘要:
Recognition of handwritten digits is a very popular application of machine learning. In this context, each of the ten digits (0-9) is defined as a class in the setting of machine learning based classification tasks. In general, popular learning methods , such as support vector machine, neural networks and K nearest neighbours, have been used for classifying instances of handwritten digits to one of the ten classes. However, due to the diversity of handwriting styles from different people, it can happen that some handwritten digits (e.g. 4 and 9) are very similar and are thus difficult to distinguish. Also, each single learning algorithm may have its own advantages and disadvantages, which means that a single algorithm would be capable of learning some but not all specific characteristics of handwritten digits. From this point of view, a method for handwritten digits recognition is proposed in the setting of ensemble learning, towards encouraging the diversity among different classifiers trained by different learning algorithms. In particular, the image features of handwritten digits are extracted by using the Convolutional Neural Network architecture. Furthermore, single classifiers trained respectively by K nearest neighbours and random forests are fused as an ensemble one. The experimental results show that the ensemble classifier was able to achieve a recognition accuracy of ≥ 98% using the MNISET data set.
摘要:
Porcine epidemic diarrhea(PED)is an acute intestinal infectious disease caused by porcine epidemic diarrhea virus(PEDV).PED occurs highly in ten days piglets,with a mortality rate of 100%.Colloidal gold immunochromatography assay and enzymelinked immunosorbent assay(ELISA)are the most widely used for the detection of PEDV.Both methods require natural antibodies whose activity are greatly affected by environmental factors seriously.So we prepare the artificial antibody of PEDV,a kind of nanomolecular imprinted polymers synthesized by solid reaction method with the epitope of PEDV as the template molecule.The antigen PEDV detected by artificial antibody through pseudo enzyme linked immunosorbent assay will be discussed.
摘要:
In this paper, we investigate the oscillation of second-order half-linear neutral dynamic equations with distributed deviating arguments of the form (r(t) |zΔ(t)|α-1 z△(t)△ +∫ba q(t,ξ)|x(g(t,ξ))|α-1 x(g(t,ξ))△ξ =0,where r(t)and p(t) are real-valued rd-continuous positive functions definedon T,z(t) =x(t) + p(t)x(τ(t)) and α is a constant with α ≥ 1.By using the generalized Riccati transformation and the inequality technique, we establish some new oscillatory criteria for all solutions to second-order half-linear neutral dynamic equations being oscillatory on the time scale T.In addition, some examples are given to illustrate our main results.
摘要:
Image segmentation is a popular application area of machine learning. In this context, each target region drawn from an image is defined as a class towards recognition of instances that belong to this region (class). In order to train classifiers that recognize the target region to which an instance belongs, it is important to extract and select features relevant to the region. In traditional machine learning, all features extracted from different regions are simply used together to form a single feature set for training classifiers, and feature selection is usually designed to evaluate the capability of each feature or feature subset in discriminating one class from other classes. However, it is possible that some features are only relevant to one class but irrelevant to all the other classes. From this point of view, it is necessary to undertake feature selection for each specific class, i.e, a relevant feature subset is selected for each specific class. In this paper, we propose the so-called multi-task feature selection approach for identifying features relevant to each target region towards effective image segmentation. This way of feature selection requires to transform a multi-class classification task into n binary classification tasks, where n is the number of classes. In particular, the Prism algorithm is used to produce a set of rules for class specific feature selection and the K nearest neighbour algorithm is used for training a classifier on a feature subset selected for each class. The experimental results show that the multi-task feature selection approach leads to an significant improvement of classification performance comparing with traditional feature selection approaches.
作者机构:
[Mansheng Chen; Chunhua Zhang; Weiwei Fu; Dongcheng Liu; Fupei Liang] Key Laboratory of Functional Organometallic Materials of Hengyang Normal University, College of Hunan Province, College of chemistry and Materials Science;[Mansheng Chen; Chunhua Zhang; Weiwei Fu; Dongcheng Liu; Fupei Liang] Key Laboratory for the Chemistry and Molecular Engineering of Medicinal Resources (Ministry of Education of China), School of Chemistry and pharmaceutical Sciences, Guangxi Normal University
会议名称:
The 4th International Congress on Advanced Materials (AM2018)
会议时间:
2018-11-15
会议地点:
中国江苏镇江
摘要:
As we know, metal-organic frameworks(MOFs) are new generation of porous materials which are constructed via the coordination bonds between metal ions/clusters and organic functional ligands.For MOFs,
作者机构:
Hengyang Normal University,School of Education Science
会议名称:
2018 International Conference on Education,Psychology,and Management Science(ICEPMS 2018)
会议时间:
2018-10-13
会议地点:
中国上海
会议论文集名称:
Proceedings of 2018 International Conference on Education,Psychology,and Management Science(ICEPMS 2018)
关键词:
Parenting Style;Junior High School Students;Emotional Adjustment Strategies
摘要:
Objective: To understand the relationship between parenting style and junior high school students’ emotional adjustment strategies. Methods: A questionnaire survey was conducted on 300 junior high school students from Hengyang Boya School by using the Parental Rearing Rating Scale revised by Yue Dongmei et al. and the Cognitive Emotion Regulation Strategy Scale revised by Dong Guangheng and others. The data were statistically analyzed. Results(1) The parenting styles used by the parents of junior high school students were emotional warmth and understanding. There were differences in parenting styles of junior high school students of different genders and grades(P<0.05, t=3.681);(2) The mood adjustment strategies of junior high school students were overally positive. There were significant differences in the emotional adjustment strategies of junior high school students of different genders and grades(P<0.05, t=-2.914), and there was no difference in whether or not the only child(P>0.05).(3) There is a significant correlation between parenting style and junior high school students’ emotional adjustment strategies. Conclusions:(1) Parents’ parenting styles of junior high school students adopt more emotional warmth and understanding of parenting styles, but they still need further adjustment in the use of other parenting styles;(2) The junior high school students’ emotional adjustment strategies are positive overall. The problems are mainly in contemplation and self-blame;(3) there is a correlation between parenting style and junior high school students’ emotional adjustment strategies.
作者:
Zhao, Hui-huang*;Liu, Han;Zheng, Jin-Hua;Fu, Bin
期刊:
2018 11TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, BIOMEDICAL ENGINEERING AND INFORMATICS (CISP-BMEI 2018),2018年:1-7
通讯作者:
Zhao, Hui-huang
作者机构:
[Zhao, Hui-huang] Hengyang Normal Univ, Coll Comp Sci & Technol, Hengyang, Peoples R China.;[Zheng, Jin-Hua; Zhao, Hui-huang] Hunan Prov Key Lab Intelligent Informat Proc & Ap, Hengyang, Hunan, Peoples R China.;[Liu, Han] Cardiff Univ, Sch Comp Sci & Informat, Cardiff, S Glam, Wales.;[Fu, Bin] Univ Texas Rio Grande Valley, Dept Comp Sci, Edinburg, TX USA.
通讯机构:
[Zhao, Hui-huang] H;Hengyang Normal Univ, Coll Comp Sci & Technol, Hengyang, Peoples R China.;Hunan Prov Key Lab Intelligent Informat Proc & Ap, Hengyang, Hunan, Peoples R China.
会议名称:
11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)
会议时间:
OCT 13-15, 2018
会议地点:
Beijing, PEOPLES R CHINA
会议主办单位:
[Zhao, Hui-huang] Hengyang Normal Univ, Coll Comp Sci & Technol, Hengyang, Peoples R China.^[Zhao, Hui-huang;Zheng, Jin-Hua] Hunan Prov Key Lab Intelligent Informat Proc & Ap, Hengyang, Hunan, Peoples R China.^[Liu, Han] Cardiff Univ, Sch Comp Sci & Informat, Cardiff, S Glam, Wales.^[Fu, Bin] Univ Texas Rio Grande Valley, Dept Comp Sci, Edinburg, TX USA.
摘要:
This paper presents an occlusion robust tracking (ORT) method for multiple faces tracking. Given a video having multiple faces, we firstly detect faces in the first frame using the off-the-shelf face detector, and then extract wavelet packet transform (WPT) coefficients and color features from the detected faces, finally we design a back propagation (BP) neural network and track the faces by a particle filter and BP neural network. The main contribution is twofold. Firstly, the WPT coefficients combined with traditional color features is utilized to face tracking. It efficiently describes faces due to their discrimination and simplicity. Secondly, we propose an improved tracking method for occlusion robust tracking based on the BP neural network. When there is an occlusion, BP neural network learns from previous tracking results and is utilized to refine the current result from particle filter. Experimental results have been shown that our ORT method can handle the occlusion effectively and achieve better performance than several previous methods.