设施农业中水分调控与水分利用效率关系研究

分析了中国设施农业发展现状及设施可控条件下作物生活因素全方位调控存在的问题.研究了作物水分利用效率与作物生产潜力、产量的关系.基于作物水分利用效率的生理生态机理,探讨了设施农业中节水灌溉对作物生活因素全方位调控的可行性.结果表明,设施农业环境中,在人工可控条件下的水分调控,将能提高作物生产潜力和节水潜力.     

设施农业中水分调控与水分利用效率关系研究

分析了中国设施农业发展现状及设施可控条件下作物生活因素全方位调控存在的问题。研究了作物水分利用效率与作物生产潜力、产量的关系。基于作物水分利用效率的生理生态机理，探讨了设施农业中节水灌溉对作物生活因素全方位调控的可行性。结果表明，设施农业环境中，在人工可控条件下的水分调控，将能提高作物生产潜力和节水潜力。     

陕西省耕地生产潜力估算

针对耕地资源分布不均、可利用地急剧缺乏等问题,研究了耕地生产潜力估算方法,有效地管理耕地资源,获取农情状况监测信息。以陕西省耕地区域为研究对象,利用10年(2003—2012年)的遥感、气象、土壤性状和基础地理数据,基于改进的"机制法"模型结合作物生长动态,实现了陕西省耕地生产潜力的估算。陕西省耕地生产潜力值的总体空间分布为北山陕北黄土高原关中及以南区域,10年间潜力值总量均大于6 000万吨,年际间变化幅度趋于水平。利用2011年统计的各市单位面积产量数据与估算的耕地生产潜力结果对比分析,其分析结果符合线性关系,R~2为0.695 5。研究结果表明,所提出的估算方法可以很好地应用于陕西省耕地生产潜力的估算,并为农情监测提供数据支撑。     

机器学习在降水预报中的应用

精准的降水预报有助于人们提前预警极端降水以减少人身和财产损失,近年来机器学习在降水预测方面具有巨大潜力。目前,针对降水预报的研究包括传统方法和机器学习方法,相比于传统方法,机器学习在降水预报方面的精度得到大幅提高。本文概括介绍了2个传统的预报方法和4个机器学习方法。     

固态降水传感器现场核查装置技术研究

针对气象观测台站固态降水传感器现场核查及测试的实际需求,研制了现场核查装置,结合砝码法实现了固态降水传感器的现场核查和测试;现场核查装置由基于ZigBee无线网络的数据获取装置和加重装置构成,数据获取装置具备环境气压、温度、相对湿度的实时检测能力,具备RS232、RS485及通断信号方式3种固态降水传感器接口的数据读取能力;加重装置由三角支架、OPD降水模拟器及砝码托盘组成,其中降水模拟器采用阻挡原有OPD降水发生探测器红外光束,人为给定指定频率脉冲信号的方法实现了降水的模拟,能够兼容多种型号的固态降水传感器;经实验测试,固态降水传感器能够准确识别加入其中的砝码重量,数据获取装置的3种接口数据读取准确度均达到100%;降水量测量值与理论值相关系数为0.9999;表明现场核查装置能够应用于固态降水传感器现场核查及测试业务。     

植被MODIS-LAI的温度降水响应

本研究首先利用贵州省2001全年基于MODIS遥感影像反演的8天一景的LAI平均资料,采用高光谱遥感数据处理分析方法对研究区地物进行分类,得到研究区植被覆盖类型结果;然后基于此分类结果,分别选取研究区19个气象站点附近各种类型植被,结合2001年贵州省温度和降水气象数据,建立了各种植被LAI与温度及降水的相关关系,用以揭示植被的季节变化对气候变化的敏感性特征响应,并从地球物理学、生态学、气候学等多个角度进一步阐明了出现相关特征的原因和物理机制。结果表明:研究区植被覆盖与温度随季节变化有显著的相关,而与降水的相关则由于植被对水分的滞后性反映则不甚显著;其中常绿林和落叶林由于较为稳固的生态环境和较少受到一些人为因素干扰而与温度和降水具有更高的相关性,而农田和草地对温度和降水的响应则更为复杂和敏感。     

改进频率分布和风速纠正的青藏高原格点降水数据集（1980~2009年）

青藏高原格点降水数据是该地区气象、水文、生态等多方面研究的重要支撑。然而,因青藏高原地形和观测条件的影响,常规的格点降水资料处理方法通常难以表征格网内降水的真实统计参数,也并未将风速影响的器测误差考虑在内。针对此问题,对降水数据进行降水观测损失订正和降水频率分布优化形成新的数据集。由于考虑了风引起的观测损失且使用了不易受到台站密度影响的插值方案,该数据的均值比国际同类数据平均偏大20%,方差偏大2倍。更大的方差,意味着该数据可以更大程度地减少低密度观测网给格点数据带来的平滑效应,对于研究气候的变化特征更有优势。该数据覆盖时间范围从1980年1月1日至2009年12月31日,时间分辨率为1 d,水平空间分辨率10 km。数据适合作为数值模式降水和卫星遥感降水频率纠正的参考数据源,也可作为各类陆面水文模型的输入参数。     

基于Matlab与VB混合编程的流域降水预报系统

利用研究区获得的水文观测资料,采用模块开发和系统集成方式,研制了研究区流域降水预报系统。介绍了系统的体系结构、主要功能、运行情况及开发的关键技术。叙述了流域降水预报的各种预报方法,并建立了基于遗传算法的降水预报神经网络模型（GA-BP网络模型）。结果表明,GA-BP网络是一种精度较高的降水预报模型,提高预测精度,增长有效预见期。该系统能根据流域观测数据、高空数据、卫星云图、数值产品等数据,实现不同数据源的信息处理和不同时效的降水预报制作,为洪水预警预报和防洪决策服务。     

水分胁迫条件下玉米生产潜力遥感评估模型——以重庆市长寿区为例

本文将WOFOST作物生长模型与遥感技术相结合,提出一种基于遥感的水分胁迫条件下玉米生产潜力评估模型,可利用遥感数据反演区域干旱强度,并驱动作物生长模型,最终得到作物生产潜力。该模型的核心是基于温度植被干旱指数(TVDI)每日蒸散算法,采用该算法可较为准确地计算水分胁迫条件下玉米农田每日蒸散量;并结合优化选取的作物品种参数,利用自行开发的TVDI-WOFOST软件开展计算,达到精确模拟干旱条件下作物产量的目的。经农业统计数据证明,本文所提出的评估模型可较好模拟水分胁迫条件下玉米生产潜力,对干旱灾情评估、农业发展规划、水利建设规划等工作具有较高的参考价值。     

基于非表面参考技术的机载双频降水反演结果分析

双频降水测量雷达是我国计划发射的风云三号降水测量卫星上的主载荷。双频测量能够较好地估计粒子谱分布参数,提高降雨率定量反演的精度,对双频降水反演算法的研究是降水产品业务化的基础。首先介绍基于非SRT的双频降水反演算法的主要原理,随后采用模拟数据对反演算法的精度进行检验,并选取机载雷达外场校飞试验中的实测数据,分析了机载雷达降雨探测的合理性。结果表明:双频反演的DSD参数基本合理,能够准确地反映出层云降水中亮带的峰值信息,并且和在轨同步观测的星载降水测量雷达PR的探测结果相近。此外,还探讨了随机选取的机载反射率因子廓线的双频反演结果以及可能引起反演误差的原因,结果发现相态转换的高度以及水的体积比可能对4 km附近及其以上的区域有一定的影响,对4 km以下的部分则影响不大。同时温度对反演结果的影响主要集中在3.5 km附近,在其他高度层,温度的影响基本可以忽略。同时降雨率的精度还受到雷达系统误差的制约。总体而言,机载双频降水反演结果具有一定的精度,基本符合当时机载外场试验的实际天气状况,从而验证了机载雷达降雨探测的合理性。     

Statistical properties of controlled fluid flows with applications to control of mixing

In this paper, we study statistical properties of fluid flows that are actively controlled. Statistical properties such as Lagrangian and Eulerian time-averages are important flow quantities in fluid flows, particularly during mixing processes. Due to the assumption of incompressibility, the transformations in the state space can be described by a sequence of measure preserving transformations on a measure space. The classical Birkhoff's pointwise ergodic theorem does not necessarily apply in the context of sequences of transformations. We call B-regular a sequence for which this theorem holds. Motivated by mixing control concepts, we define three notions of asymptotic equivalence for sequences of transformations. We show an example in which Birkhoff's pointwise ergodic theorem does not hold even when a ‘strong’ asymptotic equivalence to a B-regular sequence is assumed. Under a ‘very strong’ asymptotic equivalence condition, we prove B-regularity. In the context of optimize-then-stabilize strategy for mixing control, we also prove that very strong asymptotic equivalence to a mixing sequence implies mixing. The mean ergodic theorem and the Poincare’ recurrence theorem are also proven for sequences of transformations under suitable asymptotic equivalence assumptions.     

Describing the functional spatial structure of urban environments

People learn the layout of cities mainly through a series of trips. Wayfinders experience the city structure differently depending on the mode of transport they use. The acquired mental representation then consists of the directly observed, physically accessible parts of the city. In this paper, we propose a computational model to construct images of cities, adapting their content depending on the wayfinder’s access constraints. First, we formally study and extend the classification of Lynch’s elements of the city form. Second, we propose a simple approach to analyzing local functional relationships between these elements, as experienced by wayfinders. The study of the functional relationships allows for the construction of the most complete image of the city that might be acquired by a wayfinder with given accessibility characteristics. These representations of urban environments can support advanced spatial assistance systems and cognitively efficient spatial interfaces.     

An analysis of assembly

This paper concerns the problem of assembling composite objects. We study the problem on two fronts; Firstly we consider the complexity of deciding the existence of an assembly sequence and show that this is PSPACE-hard in general. Secondly we define a new measure of complexity, one that attempts to measure the minimum number of hands required to assemble a given composite. We analyze various classes of composite objects with respect to this measure.     

Quantitative logic

In this paper, we introduce the concept of the degree of the truth in the framework of so called many-valued propositional logic systems with the intention of measuring to what extent a given formula is true. Such a concept can indeed induce, in a very natural way, the degree of the similarity as well as to induce a pseudo-metric among formulas as the ‘graded’ version of the notion of the logical equivalence. The basic properties of such induced logic metric space hence are investigated in this paper. We further introduce different concepts of the degree of the divergence and the degree of the consistency in order to grade the extent of the consistency of a logic theory. To the end, all the basic logic notions are graded. Lastly, we propose in this paper three patterns of ‘approximate reasoning’ so far as the many-valued propositional logic systems are concerned. Hence, we can claim that we have laid the foundation for the “quantitative logic”. Since this theory has touched upon several key concepts of similarity, comparison, measurements, etc. in information theory, we are convinced that the theory may have profound impact in contemporary information technology. In addition, quantitative logic can be regarded as a highly representative example of mathematics of uncertainty capable of handling vagueness.     

The semantics of the combination of atomized statements and parallel choice

In this paper we define a uniform language that is an extension of the language underlying the process algebraPA. One of the main extensions of this language overPA is given by so-called atomizing brackets. If we place these brackets around a statement then we treat this statement as an atomic action. Put differently, these brackets remove all interleaving points. We present a transition system for the language and derive its operational semantics. We show that there are several options for defining a transition system such that the resulting operational semantics is a conservative extension of the semantics forPA. We define a semantic domain and a denotational model for the language. Next we define a closure operator on the semantic domain and show how to use this closure operator to derive a fully abstract denotational semantics. Then the algebraic theory of the language is considered. We define a collection of axioms and a term rewrite system based on these axioms. Using this term rewrite system we are able to identify normal forms for the language. It is shown that these axioms capture the denotational equality. It follows that if two terms are provably equal then they have the same operational semantics. Finally, we show how to extend the axiomatization in order to axiomatize its operational equivalence.     

Integration of Cloud computing and Internet of Things: A survey

Cloud computing and Internet of Things (IoT) are two very different technologies that are both already part of our life. Their adoption and use are expected to be more and more pervasive, making them important components of the Future Internet. A novel paradigm where Cloud and IoT are merged together is foreseen as disruptive and as an enabler of a large number of application scenarios.In this paper, we focus our attention on the integration of Cloud and IoT, which is what we call the CloudIoT paradigm. Many works in literature have surveyed Cloud and IoT separately and, more precisely, their main properties, features, underlying technologies, and open issues. However, to the best of our knowledge, these works lack a detailed analysis of the new CloudIoT paradigm, which involves completely new applications, challenges, and research issues. To bridge this gap, in this paper we provide a literature survey on the integration of Cloud and IoT. Starting by analyzing the basics of both IoT and Cloud Computing, we discuss their complementarity, detailing what is currently driving to their integration. Thanks to the adoption of the CloudIoT paradigm a number of applications are gaining momentum: we provide an up-to-date picture of CloudIoT applications in literature, with a focus on their specific research challenges. These challenges are then analyzed in details to show where the main body of research is currently heading. We also discuss what is already available in terms of platforms–both proprietary and open source–and projects implementing the CloudIoT paradigm. Finally, we identify open issues and future directions in this field, which we expect to play a leading role in the landscape of the Future Internet.     

New spectral lower bounds on the bisection width of graphs

The communication overhead is a major bottleneck for the execution of a process graph on a parallel computer system. In the case of two processors, the minimization of the communication can be modeled using the graph bisection problem. The spectral lower bound of λ₂|V|/4 for the bisection width of a graph is widely known. The bisection width is equal to λ₂|V|/4 iff all vertices are incident to λ₂/2 cut edges in every optimal bisection.

We present a new method of obtaining tighter lower bounds on the bisection width. This method makes use of the level structure defined by the bisection. We define some global expansion properties and we show that the spectral lower bound increases with this global expansion. Under certain conditions we obtain a lower bound depending on λ₂^β|V| with . We also present examples of graphs for which our new bounds are tight up to a constant factor. As a by-product, we derive new lower bounds for the bisection widths of 3- and 4-regular Ramanujan graphs.     

An approach for ranking of fuzzy numbers

In order to rank all fuzzy numbers, we modify the method of “a new approach for ranking of trapezoidal fuzzy numbers” by Abbasbandy and Hajjari (2009). Our proposed method is used for ranking symmetric fuzzy numbers. The advantage of this method is illustrated by some comparative examples.     

On Restricted-Focus-of-Attention Learnability of Boolean Functions

In the k-Restricted-Focus-of-Attention (k-RFA) model, only k of the n attributes of each example are revealed to the learner, although the set of visible attributes in each example is determined by the learner. While thek -RFA model is a natural extension of the PAC model, there are also significant differences. For example, it was previously known that learnability in this model is not characterized by the VC-dimension and that many PAC learning algorithms are not applicable in the k-RFA setting.In this paper we further explore the relationship between the PAC and k -RFA models, with several interesting results. First, we develop an information-theoretic characterization of k-RFA learnability upon which we build a general tool for proving hardness results. We then apply this and other new techniques for studying RFA learning to two particularly expressive function classes,k -decision-lists (k-DL) and k-TOP, the class of thresholds of parity functions in which each parity function takes at most k inputs. Among other results, we prove a hardness result for k-RFA learnability of k-DL,k n-2 . In sharp contrast, an (n-1)-RFA algorithm for learning (n-1)-DL is presented. Similarly, we prove that 1-DL is learnable if and only if at least half of the inputs are visible in each instance. In addition, we show that there is a uniform-distribution k-RFA learning algorithm for the class of k -DL. For k-TOP we show weak learnability by ak -RFA algorithm (with efficient time and sample complexity for constant k) and strong uniform-distribution k-RFA learnability of k-TOP with efficient sample complexity for constant k. Finally, by combining some of our k-DL and k-TOP results, we show that, unlike the PAC model, weak learning does not imply strong learning in the k -RFA model.     

The cost of probabilistic agreement in oblivious robot networks

In this paper, we look at the time complexity of two agreement problems in networks of oblivious mobile robots, namely, at the gathering and scattering problems. Given a set of robots with arbitrary initial locations and no initial agreement on a global coordinate system, gathering requires that all robots reach the exact same but not predetermined location. In contrast, scattering requires that no two robots share the same location. These two abstractions are fundamental coordination problems in cooperative mobile robotics. Oblivious solutions are appealing for self-stabilization since they are self-stabilizing at no extra cost. As neither gathering nor scattering can be solved deterministically under arbitrary schedulers, probabilistic solutions have been proposed recently.The contribution of this paper is twofold. First, we propose a detailed time complexity analysis of a modified probabilistic gathering algorithm. Using Markov chains tools and additional assumptions on the environment, we prove that the convergence time of gathering can be reduced from O(n²) (the best known bound) to O(1) or , depending on the model of multiplicity detection. Second, using the same technique, we prove that scattering can also be achieved in fault-free systems with the same bounds.