Investigation of remote sensing techniques of measuring soil moisture

Major activities described include development and evaluation of theoretical models that describe both active and passive microwave sensing of soil moisture, the evaluation of these models for their applicability, the execution of a controlled field experiment during which passive microwave measurements were acquired to validate these models, and evaluation of previously acquired aircraft microwave measurements. The development of a root zone soil water and soil temperature profile model and the calibration and evaluation of gamma ray attenuation probes for measuring soil moisture profiles are considered. The analysis of spatial variability of soil information as related to remote sensing is discussed as well as the implementation of an instrumented field site for acquisition of soil moisture and meteorologic information for use in validating the soil water profile and soil temperature profile models

An email classification model based on rough set theory

The communication via email is one of the most popular services of the Internet. Emails have brought us great convenience in our daily work and life. However, unsolicited messages or spam, flood our email boxes, which results in bandwidth, time and money wasting. To this end, this paper presents a rough set based model to classify emails into three categories - spam, no-spam and suspicious, rather than two classes (spam and non-spam) in most currently used approaches. By comparing with popular classification methods like Naive Bayes classification, the error ratio that a non-spam is discriminated to spam can be reduced using our proposed model.<br /

Rough Set Classifier Based on DSmT

International audienceThe classifier based on rough sets is widely used in pattern recognition. However, in the implementation of rough set-based classifiers, there always exist the problems of uncertainty. Generally, information decision table in Rough Set Theory (RST) always contains many attributes, and the classification performance of each attribute is different. It is necessary to determine which attribute needs to be used according to the specific problem. In RST, such problem is regarded as attribute reduction problems which aims to select proper candidates. Therefore, the uncertainty problem occurs for the classification caused by the choice of attributes. In addition, the voting strategy is usually adopted to determine the category of target concept in the final decision making. However, some classes of targets cannot be determined when multiple categories cannot be easily distinguished (for example, the number of votes of different classes is the same). Thus, the uncertainty occurs for the classification caused by the choice of classes. In this paper, we use the theory of belief functions to solve two above mentioned uncertainties in rough set classification and rough set classifier based on Dezert-Smarandache Theory (DSmT) is proposed. It can be experimentally verified that our proposed approach can deal efficiently with the uncertainty in rough set classifiers

Did the Decline in Social Capital Decrease American Happiness? A Relational Explanation of the Happiness Paradox

Most popular explanations of the happiness paradox cannot fully account for the lack of growth in U.S. reported well-being during the last thirty years (Blanchflower and Oswald (2004)). In this paper we test an alternative hypothesis, namely that the decline in U.S. social capital is responsible for what is left unexplained by previous research. We provide three main findings. First, we show that the inclusion of social capital does improve the account of reported happiness. Second, we provide evidence of a decline in social capital indicators for the period 1975-2004, confirming Putnam's claim (Putnam (2000)). Finally, we show that failed growth of happiness is largely due to the decline of social capital and, in particular, to the decline of its relational and intrinsically motivated component.happiness, social capital, economic growth, relational goods, instrinsic motivations

Two-tier channel estimation aided near-capacity MIMO transceivers relying on norm-based joint transmit and receive antenna selection

We propose a norm-based joint transmit and receive antenna selection (NBJTRAS) aided near-capacity multiple-input multiple-output (MIMO) system relying on the assistance of a novel two-tier channel estimation scheme. Specifically, a rough estimate of the full MIMO channel is first generated using a low-complexity, low-training-overhead minimum mean square error based channel estimator, which relies on reusing a modest number of radio frequency (RF) chains. NBJTRAS is then carried out based on this initial full MIMO channel estimate. The NBJTRAS aided MIMO system is capable of significantly outperforming conventional MIMO systems equipped with the same modest number of RF chains, while dispensing with the idealised simplifying assumption of having perfectly known channel state information (CSI). Moreover, the initial subset channel estimate associated with the selected subset MIMO channel matrix is then used for activating a powerful semi-blind joint channel estimation and turbo detector-decoder, in which the channel estimate is refined by a novel block-of-bits selection based soft-decision aided channel estimator (BBSB-SDACE) embedded in the iterative detection and decoding process. The joint channel estimation and turbo detection-decoding scheme operating with the aid of the proposed BBSB-SDACE channel estimator is capable of approaching the performance of the near-capacity maximumlikelihood (ML) turbo transceiver associated with perfect CSI. This is achieved without increasing the complexity of the ML turbo detection and decoding process

Development of an early warning system of crop moisture conditions using passive microwave

Emissivities were calculated from the Nimbus 5 electrically scanning microwave radiometer (ESMR) over 25 km grid cells for the southern Great Plains includin the western two-thirds of Kansas and Oklahoma and northwest Texas. These emissivities, normalized for seasonal temperature changes, were in excellent agreement with theory and measurements made from aircraft and truck sensors at the 1.55 cm wavelength of ESMR. These emissivities were related to crop moisture conditions of the winter wheat in the major wheat producing counties of the three states. High correlations were noted between emissitivity and an antecedent precipitation index (API) used to infer soil moisture for periods when the soils were essentially bare. The emissivities from ESMR were related through API and actual crop condition reports to progress of fall planting, adequacy of crop moisture for stand establishment, and periods of excessive moisture that necessitated replanting. Periods of prolonged frozen soil in the winter were observable at several grid points. The average emissivities of the canopy/soil surface during the maximum canopy development times in the spring showed a good agreement with moisture stress inferred from rainfall and yield data

A Reconstruction of the ‘Classical’ Linguistic Transformation Theory CLT

We reconstruct “the classical transformational theory” of Chomsky, and fit it into the structuralist theory of science. We describe both the formal and the empirical features of this classical account, so that one basic hypothesis of this theory – where central notions are used – can be formulated, and in which Chomsky’s “classical” distinction between surface structure and deep structure is clarified. In the empirical claim of this theory are words, sentences and high-structured entities in an inseparable way intertwined. We claim that the formal structure of a natural language is not approximately the same as that of an empirical theory in general. We clarify two special points which affect the structure of the notion of an empirical theory, namely: the delineation of intended applications and the fit between data and models. We hold that the concept of the empirical claim for a linguistic theory should be generalized in comparison with the “standard” structuralist approach.Fil: Gonzalo, Adriana Noemi. Universidad Nacional del Litoral. Facultad de Humanidades y Ciencias. Departamento de Filosofía; ArgentinaFil: Balzer, Wolfgang. Universitat Genzentrum Der Ludwing-maximilians; Alemani

Microwave soil moisture measurements and analysis

An effort to develop a model that simulates the distribution of water content and of temperature in bare soil is documented. The field experimental set up designed to acquire the data to test this model is described. The microwave signature acquisition system (MSAS) field measurements acquired in Colby, Kansas during the summer of 1978 are pesented

Quantity and number

Quantity is the first category that Aristotle lists after substance. It has extraordinary epistemological clarity: "2+2=4" is the model of a self-evident and universally known truth. Continuous quantities such as the ratio of circumference to diameter of a circle are as clearly known as discrete ones. The theory that mathematics was "the science of quantity" was once the leading philosophy of mathematics. The article looks at puzzles in the classification and epistemology of quantity