作者机构：
[Cao Xiao-lan; Deng Meng-jie] Hunan Agr Univ, Coll Informat Sci & Technol, Changsha 410128, Hunan, Peoples R China.;[Cao Xiao-lan; Cui Guo-xian] Hunan Agr Univ, Ramie Res Inst, Changsha 410128, Hunan, Peoples R China.
通讯机构：
[Cui Guo-xian] H;Hunan Agr Univ, Ramie Res Inst, Changsha 410128, Hunan, Peoples R China.
关键词：
苎麻;高光谱;主成分分析;判别分析
摘要：
苎麻(Boehmeiria nivea L)是我国的特产,作为一种传统的纤维作物,一直有着较高的经济地位。开发一种基于高光谱的、新型高效的苎麻品种识别方法,有利于苎麻栽种、种质资源开发利用,为实现苎麻高产优质及麻田精准管理提供关键技术支撑,对提高苎麻产量和品质有重要意义。为了将高光谱技术应用于苎麻品种识别,采集了9个不同基因型苎麻品种,利用地物光谱仪测定苎麻叶片高光谱反射率,共1 458个叶片高光谱数据,利用主成分分析(PCA)对高光谱数据进行降维,探讨PCA最佳主因子个数的确定方法,比较不同主因子个数与不同判别分析(DA)方法———即线性判别分析(LDA)、二次判别分析(QDA)和马氏距离判别分析(MD-DA)组合,在建立基于叶片高光谱的苎麻品种识别模型中效果。对全波段的数据样本进行主成分分析之后,以2~20个主成分作为特征变量,分别建立LDA,QDA和MD-DA三种品种判别模型进行预测,以预测集正确率为评价标准,比较各种组合的效果。结果表明,若以累积贡献率≥85%为标准,选择2个主成分时,LDA,QDA和MD-DA三种判别模型预测集正确率分别为32.92%,38.48%和33.54%;以特征值≥1为标准,选择11个主成分时,三种判别模型预测集正确率分别为68.72%,87.04%和83.54%;若以预测集正确率为优先考虑标准,将主成分个数增加至20个时,三种判别模型正确率有较大提高,分别为84.98%,95.68%和95.27%。由此,得到如下结论:①利用PCA组合DA方法建立基于苎麻叶片高光谱的品种识别模型是可行的,但因子数不同、DA判别标准不同、组合方法不同效果差异非常大;②主因子个数对识别结果的影响较为明显,适当增加主成分个数可以显著提高模型判别正确率,因此不应局限于PCA特征值和方差累积贡献率的选择方法;③主因子个数相同时,三种判别标准中,QDA效果最好, LDA效果最差;④最佳组合是20个主成分+QDA方法,其数据维度大大降低(由全波段的2 031维降低20维),而预测集正确率为95.68%。 <&wdkj&>Ramie(Boehmeiria nivea L)is a special and traditional fiber crop in China,having higher economic status.Determining the hyperspectral reflectance of ramie leaves with the spectrometer and developing a hyperspectrum-based method of ramie variety identification of high efficiency will be beneficial for the cultivation of ramie,the development and utilization of germplasm resources as well as the provision of critical technological supports to realize the top quality and high production of ramie and the accurate management of ramie croplands,which are significant for improving ramie yield and quality.In order to apply the hyperspectral technology for identifying ramie varieties,total 1458hyperspectral data on the ramie leaves coming from nine ramie varieties of different genotypes were collected.According to these data,we explored the using of the Principal Components Analysis(PCA)to reduce dimensions of the hyperspectral data and how to determine the best appropriate number of principal factors in the PCA.Further,we compared different combinations constituted by different principal factors and different Discriminant Analysis approaches,and the results of the ramie variety identifying models based on the hyperspectrum of ramie leaves were established.After the principal component analysis of the full-band data sample,with 2~20principal components as the feature variables,we applied three discriminant models,namely the Linear Discriminant analysis(LDA),the Quadratic Discriminant Analysis(QDA),and the Mahalanobis Distance Discriminant Analysis,(MD-DA),to create variety discriminant models and used them to predict,and with the accuracy of the prediction set as the evaluation criteria,the effects of various combinations were compared.The results showed that when we used the cumulative contribution rate(≥85%)as the criteria and selected two principal components,the accuracies for the LDA,the QDA and the MD-DA prediction sets were respectively 32.92%, 38.48%and 33.54%;but,when we used the feature value(≥1)as the criteria,and selected eleven principal components,the accuracies for the prediction sets of above discriminant models were respectively 68.72%,87.04%and 83.54%;and further, when we considered the accuracy of the prediction set as the preferential criteria and selected twenty principal components,the accuracies for above discriminant models were all significantly improved and were respectively 84.98%,95.68%and 95.27%. Therefore,we can draw the following conclusions:(1)it is feasible to establish the ramie leaf-based hyperspectral variety identification model by combining the PCA and the DA,but there are big differences between results due to different numbers of factors, different DA criterias and different combination approaches;(2)The impact of the number of principal factors on the identification results are significant,and the appropriate adding of the principal components can notably improve the accuracies of corresponding models,thus it is not confined to how to select the feature values of the PCA and the accumulative variance contribution rate;(3)When the numbers of principal factors are the same,among above three discriminant criteria,the effect of the QDA is the best while that of the LDA is the worst;(4)Twenty principal components and the QDA approach constitute the best combination,which makes data dimensions be hugely reduced,from 2031dimensions of the full-band down to 20dimensions, and the accuracy of the prediction set is 95.68%.
作者机构：
[谭泗桥] chool of Information Science and Technology, Hunan Agricultural University, Changsha, 410128, China;[艾陈] College of Medicine, Shaoyang University, Shaoyang, 422000, China;[张席] College of Plant Protection, Hunan Agricultural University, Changsha, 410128, China;[李钎; 谭泗桥; 张席] Hunan Engineer Research Center for Information Technology in Agriculture, Changsha, 410128, China
通讯机构：
College of Medicine, Shaoyang University, Shaoyang, China
作者机构：
[Shi, Jian] Post Doctoral Mobile Station of Clinical Medicine, Third Xiangya Hospital, Central South University, Changsha, Hunan, 410013, China;[Feng, Li] School of Pharmaceutical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, 510006, China;[Liu, Bo] Department of Internet of Things Engineering, School of Information Science and Technology, Hunan Agricultural University, Changsha, Hunan, 410128, China;[Deng, Yunlong] Third Xiangya Hospital, Central South University, Changsha, Hunan, 410013, China
关键词：
Early recognition;Management model;Mental symptoms;Neural network algorithm
摘要：
Early intervention in time helps to improve the prognosis of schizophrenia, and it is particularly important to improve the identification and diagnosis of psychiatric risk syndrome. In this paper, the author analyse the early recognition and efficacy evaluation of mental disorders based on cultural algorithm neural network. Early assessment and intervention can effectively reduce the risk of occurrence of dangerous behaviour. In summary, through the establishment of integrated prevention and control management model, and the early identification and intervention of risk behaviours of mental patients in the study area, we can make the patients with dangerous behaviour spirit get timely, systematic, scientific and effective treatment management in the community.
关键词：
Knowledge graph;Agricultural thesaurus;Schema layer;Triple;Mathematical model
摘要：
Google proposed the concept of knowledge graph to improve the quality of searching results in 2012, so the knowledge graph brought a hot topic in the field of academic and industry. The knowledge graph can effectively improve the searching quality and the accuracy of Q & A system, which is a hot issue. With the help of agricultural experts, this paper based on the Agricultural Thesaurus, determines the rules for judging whether a thesaurus is a concept or an entity, establishes maps from Agricultural Thesaurus to the agricultural knowledge graph schema layer and the data layer. Therefore, the large-scale automatic building is realized from the Agricultural Thesaurus to the agricultural knowledge graph. In order to effectively manage and utilize triples, this paper proposes a mathematical model for the management of triples with the RDF-based triple storage pattern, which lays the solid foundation for the semantic-based agricultural information retrieving and the construction of the Q & A system.
期刊：
Journal of Computational Methods in Sciences and Engineering,2016年16(2):369-377 ISSN：1472-7978
通讯作者：
Fang, Kui
作者机构：
[Fang, Kui; Yu, Hexiang] Information Science and Technology Institute, Hunan Agricultural University, Changsha, Hunan, China;[Fang, Kui; Yu, Hexiang] College of Resources and Environment, Hunan Agricultural University, Changsha, Hunan, China
通讯机构：
Information Science and Technology Institute, Hunan Agricultural University, Changsha, Hunan, China
关键词：
Depth measurement;clarity-evaluation;gradient;optical field focusing
关键词：
Cache;Multi-core;task scheduling;schedule length;average response time
摘要：
In the past few years, multi-core processors incorporating four, six, eight, or more cores on a single die have become ubiquitous. Those cores, having their own private caches, often share a higher level cache memory, which leads to compete among different tasks. This can seriously affect the average performance of multi-core systems as the probability of cache hit could be lowered. In realizing this, we study the problem of scheduling bag-of-tasks (BoT) applications with shared cache constraint on multi-core systems. We first use cache space isolation techniques to divide shared caches into partitions. Then, we give a motivational example and outline the shared cache aware scheduling problem of multi-core systems. Finally, to provide an optimum solution for this problem, we propose a heuristic shared cache contention aware scheduling (SCAS) algorithm on multi-core systems. Our extensive simulation performance evaluation study clearly demonstrate that our proposed SCAS algorithm outperforms the existing traditional scheduling algorithm Min-min and the modified algorithm MSCAS in terms of schedule length and average response time.
摘要：
Multi-proxy signature is a variant of proxy signature, which allows that a delegator may delegate his signing rights to many proxy signers. Compared with proxy signature, multi-proxy signature can effectively prevent that some of proxy signers abuse signing rights. In this paper, we propose an efficient multi-proxy signature scheme in the standard model, which is based on the Waters’ signature scheme. Compared with other multi-proxy signature schemes in the standard model, the proposed scheme further reduces the amount of computations and communications.
关键词：
Almost periodic solution;Exponential dichotomy;Multidirectional associative memory neural networks;Multistability
摘要：
In this paper, the multiplicity of almost periodic solutions is studied for a multidirectional associative memory (MAM) neural network with almost periodic coefficients and continuously distributed delays. Under some assumptions on activation functions, some invariant subsets of the MAM neural network are constructed. The existence of multiple almost periodic solutions are obtained by using the theory of exponential dichotomy and Schauder's fixed point theorem. Furthermore, a sufficient condition is derived for the local exponential stability of some almost periodic solutions and their exponential attracting domains are also given. An example is given to illustrate the effectiveness of the results. (C) 2015 Elsevier B.V. All rights reserved.
摘要：
A multidirectional associative memory (MAM) neural network with periodic coefficients and distributed delays is studied. By constructing a Poincaré mapping, some sufficient conditions are obtained ensuring existence, uniqueness and the global exponential stability of a periodic solution of MAM neural network. The result is new to MAM neural networks. An example is given to illustrate the effectiveness of the result.
