A model of mixed signals with applications to countersignaling an the GED

We develop a job-market signaling model where signals may convey two pieces of information. This model is employed to study the GED exam and countersignaling (signals non-monotonic in ability). A result of the model is that countersignaling is more expected to occur in jobs that require a combination of skills that differs from the combination used in the schooling process. The model also produces testable implications consistent with evidence on the GED: (i) it signals both high cognitive and low non-cognitive skills and (ii) it does not affect wages. Additionally, it suggests modifications that would make the GED a more signal.

An embedded 1149.4 extension to support mixed-signal debugging

Debugging electronic circuits is traditionally done with bench equipment directly connected to the circuit under debug. In the digital domain, the difficulties associated with the direct physical access to circuit nodes led to the inclusion of resources providing support to that activity, first at the printed circuit level, and then at the integrated circuit level. The experience acquired with those solutions led to the emergence of dedicated infrastructures for debugging cores at the system-on-chip level. However, all these developments had a small impact in the analog and mixed-signal domain, where debugging still depends, to a large extent, on direct physical access to circuit nodes. As a consequence, when analog and mixed-signal circuits are integrated as cores inside a system-on-chip, the difficulties associated with debugging increase, which cause the time-to-market and the prototype verification costs to also increase. The present work considers the IEEE1149.4 infrastructure as a means to support the debugging of mixed-signal circuits, namely to access the circuit nodes and also an embedded debug mechanism named mixed-signal condition detector, necessary for watch-/breakpoints and real-time analysis operations. One of the main advantages associated with the proposed solution is the seamless migration to the system-on-chip level, as the access is done through electronic means, thus easing debugging operations at different hierarchical levels.

Detection of nitrogen deficiency in wheat from spectral reflectance indices and basic crop eco-physiological concepts

We tested the capacity of several published multispectral indices to estimate the nitrogen nutrition of wheat canopies grown under different levels of water supply and plant density and derived a simple canopy reflectance index that is greatly independent of those factors. Planar domain geometry was used to account for mixed signals from the canopy and soil when the ground cover was low. A nitrogen stress index was developed, which adjusts shoot %N for plant biomass and area, thereby accounting for environmental conditions that affect growth, such as crop water status. The canopy chlorophyll content index (CCCi) and the modified spectral ratio planar index (mSRPi) could explain 68 and 69% of the observed variability in the nitrogen nutrition of the crop as early as Zadoks 33, irrespective of water status or ground cover. The CCCi was derived from the combination of 3 wavebands 670, 720 and 790 nm, and the mSRPi from 445, 705 and 750 nm, together with broader bands in the NIR and RED. The potential for their spatial application over large fields/paddocks is discussed.

Secure Transmission in Cooperative Networks with Weak Eavesdroppers

In this letter, we propose a scheme to improve the secrecy rate of cooperative networks using Analog Network Coding (ANC). ANC mixes the signals in the air; the desired signal is then separated out, from the mixed signals, at the legitimate receiver using techniques like self interference subtraction and signal nulling, thereby achieving better secrecy rates. Assuming global channel state information, memoryless adversaries and the decode-and-forward strategy, we seek to maximize the average secrecy rate between the source and the destination, subject to an overall power budget. Then, exploiting the structure of the optimization problem, we compute its optimal solution. Finally, we use numerical evaluations to compare our scheme with the conventional approaches.

基于信息重建技术的地震信号处理方法研究

The dissertation addressed the problems of signals reconstruction and data restoration in seismic data processing, which takes the representation methods of signal as the main clue, and take the seismic information reconstruction (signals separation and trace interpolation) as the core. On the natural bases signal representation, I present the ICA fundamentals, algorithms and its original applications to nature earth quake signals separation and survey seismic signals separation. On determinative bases signal representation, the paper proposed seismic dada reconstruction least square inversion regularization methods, sparseness constraints, pre-conditioned conjugate gradient methods, and their applications to seismic de-convolution, Radon transformation, et. al. The core contents are about de-alias uneven seismic data reconstruction algorithm and its application to seismic interpolation. Although the dissertation discussed two cases of signal representation, they can be integrated into one frame, because they both deal with the signals or information restoration, the former reconstructing original signals from mixed signals, the later reconstructing whole data from sparse or irregular data. The goal of them is same to provide pre-processing methods and post-processing method for seismic pre-stack depth migration. ICA can separate the original signals from mixed signals by them, or abstract the basic structure from analyzed data. I surveyed the fundamental, algorithms and applications of ICA. Compared with KL transformation, I proposed the independent components transformation concept (ICT). On basis of the ne-entropy measurement of independence, I implemented the FastICA and improved it by covariance matrix. By analyzing the characteristics of the seismic signals, I introduced ICA into seismic signal processing firstly in Geophysical community, and implemented the noise separation from seismic signal. Synthetic and real data examples show the usability of ICA to seismic signal processing and initial effects are achieved. The application of ICA to separation quake conversion wave from multiple in sedimentary area is made, which demonstrates good effects, so more reasonable interpretation of underground un-continuity is got. The results show the perspective of application of ICA to Geophysical signal processing. By virtue of the relationship between ICA and Blind Deconvolution , I surveyed the seismic blind deconvolution, and discussed the perspective of applying ICA to seismic blind deconvolution with two possible solutions. The relationship of PC A, ICA and wavelet transform is claimed. It is proved that reconstruction of wavelet prototype functions is Lie group representation. By the way, over-sampled wavelet transform is proposed to enhance the seismic data resolution, which is validated by numerical examples. The key of pre-stack depth migration is the regularization of pre-stack seismic data. As a main procedure, seismic interpolation and missing data reconstruction are necessary. Firstly, I review the seismic imaging methods in order to argue the critical effect of regularization. By review of the seismic interpolation algorithms, I acclaim that de-alias uneven data reconstruction is still a challenge. The fundamental of seismic reconstruction is discussed firstly. Then sparseness constraint on least square inversion and preconditioned conjugate gradient solver are studied and implemented. Choosing constraint item with Cauchy distribution, I programmed PCG algorithm and implement sparse seismic deconvolution, high resolution Radon Transformation by PCG, which is prepared for seismic data reconstruction. About seismic interpolation, dealias even data interpolation and uneven data reconstruction are very good respectively, however they can not be combined each other. In this paper, a novel Fourier transform based method and a algorithm have been proposed, which could reconstruct both uneven and alias seismic data. I formulated band-limited data reconstruction as minimum norm least squares inversion problem where an adaptive DFT-weighted norm regularization term is used. The inverse problem is solved by pre-conditional conjugate gradient method, which makes the solutions stable and convergent quickly. Based on the assumption that seismic data are consisted of finite linear events, from sampling theorem, alias events can be attenuated via LS weight predicted linearly from low frequency. Three application issues are discussed on even gap trace interpolation, uneven gap filling, high frequency trace reconstruction from low frequency data trace constrained by few high frequency traces. Both synthetic and real data numerical examples show the proposed method is valid, efficient and applicable. The research is valuable to seismic data regularization and cross well seismic. To meet 3D shot profile depth migration request for data, schemes must be taken to make the data even and fitting the velocity dataset. The methods of this paper are used to interpolate and extrapolate the shot gathers instead of simply embedding zero traces. So, the aperture of migration is enlarged and the migration effect is improved. The results show the effectiveness and the practicability.

Sistema inteligente para determinação das direções de chegada de múltiplos sinais em arranjos de antenas

This dissertation presents a new proposal for the Direction of Arrival (DOA) detection problem for more than one signal inciding simultaneously on an antennas array with linear or planar geometry by using intelligent algorithms. The DOA estimator is developed by using techniques of Conventional Beam-forming (CBF), Blind Source Separation (BSS), and the neural estimator MRBF (Modular Structure of Radial Basis Functions). The developed MRBF estimator has its capacity extended due to the interaction with the BSS technique. The BSS makes an estimation of the steering vectors of the multiple plane waves that reach the array in the same frequency, that means, obtains to separate mixed signals without information a priori. The technique developed in this work makes possible to identify the multiple sources directions and to identify and to exclude interference sources

Projeto e Implementação em Ambiente Foundation Fieldbus de Filtragem Estocástica Baseada em Análise de Componentes Independentes (M175)

This work considers the development of a filtering system composed of an intelligent algorithm, that separates information and noise coming from sensors interconnected by Foundation Fieldbus (FF) network. The algorithm implementation will be made through FF standard function blocks, with on-line training through OPC (OLE for Process Control), and embedded technology in a DSP (Digital Signal Processor) that interacts with the fieldbus devices. The technique ICA (Independent Component Analysis), that explores the possibility of separating mixed signals based on the fact that they are statistically independent, was chosen to this Blind Source Separation (BSS) process. The algorithm and its implementations will be Presented, as well as the results

Coccoliths and carbonate grain-size compositions in sediment samples from the Mid-Atlantic Ridge

This study presents a differentiated carbonate budget for marine surface sediments from the Mid-Atlantic Ridge of the South Atlantic, with results based on carbonate grain-size composition. Upon separation into sand, silt, and clay sub-fractions, the silt grain-size distribution was measured using a SediGraph 5100. We found regionally characteristic grain-size distributions with an overall minimum at 8 µm equivalent spherical diameter (ESD). SEM observations reveal that the coarse particles (>8 µm ESD) are attributed to planktic foraminifers and their fragments, and the fine particles (<8 µm ESD) to coccoliths. On the basis of this division, the regional variation of the contribution of foraminifers and coccoliths to the carbonate budget of the sediments are calculated. Foraminifer carbonate dominates the sediments in mesotropic regions whereas coccoliths contribute most carbonate in oligotrophic regions. The grain size of the coccolith share is constant over water depth, indicating a lower susceptibility for carbonate dissolution compared to foraminifers. Finally, the characteristic grain-size distribution in fine silt (<8 µm ESD) is set into context with the coccolith assemblage counted and biometrically measured using a SEM. The coccoliths present in the silt fraction are predominantly large species (length > 4 µm). Smaller species (length < 4 µm) belong to the clay fraction (<2 µm ESD). The average length of most frequent coccolith species is connected to prominent peaks in grain-size distributions (ESD) with a shape factor. The area below Gaussian distributions fitted to these peaks is suggested as a way to quantitatively estimate the carbonate contribution of single coccolith species more precisely compared to conventional volume estimates. The quantitative division of carbonate into the fraction produced by coccoliths and that secreted by foraminifers enables a more precise estimate for source/sink relations of consumed and released CO2 in the carbon cycle. The allocation of coccolith length and grain size (ESD) suggests size windows for the separation or accumulation of distinct coccolith species in investigations that depend on non to slightly-mixed signals (e.g., isotopic studies).

The Battle of the Bulge: The Surprising Last Stand Against State Marijuana Legalization

Although marijuana possession remains a federal crime, twenty-three states now allow use of marijuana for medical purposes and four states have adopted tax-and-regulate policies permitting use and possession by those twenty-one and over. In this article, I examine recent developments regarding marijuana regulation. I show that the Obama administration, after initially sending mixed signals, has taken several steps indicating an increasingly accepting position toward marijuana law reform in states; however the current situation regarding the dual legal status of marijuana is at best an unstable equilibrium. I also focus on what might be deemed the last stand of marijuana-legalization opponents, in the form of lawsuits filed by several states, sheriffs, and private plaintiffs challenging marijuana reform in Colorado (and by extension elsewhere). This analysis offers insights for federalism scholars regarding the speed with which marijuana law reform has occurred, the positions taken by various state and federal actors, and possible collaborative federalism solutions to the current state-federal standoff.

Mixed colonies of two species of congeneric stingless bees (Hymenoptera: Apinae, Meliponini) display environmentally-acquired and endogenously-produced recognition signals

Nestmate recognition is fundamental for the maintenance of social organization in insect nests. It is becoming well recognized that cuticle hydrocarbons mediate the recognition process, although the origin of recognition cues in stingless bees remains poorly explored. The present study investigates the effects of endogenously-produced and environmentally-acquired components in cuticular hydrocarbons in stingless bees. The tests are conducted using colonies of Plebeia droryana Friese and Plebeia remota Holmberg. Recognition tests are performed with four different groups: conspecific nestmates, conspecific non-nestmates, heterospecifics and conspecific, genetically-related individuals that emerge in a heterospecific nest. This last group is produced by introducing brood cells of P. droryana into a P. remota colony, and the resulting adult bees are tested for acceptance 10 days after emergence. For all groups, 15 individuals are sampled for chemical analysis. The results show the acceptance of all conspecific nestmates, and the rejection of almost every conspecific non-nestmate and every heterospecific bee. Genetically-related individuals emerging from heterospecific nests present intermediate rejection (66.7% rejection). Chemical analysis shows that P. droryana individuals emerging in a P. remota nest have small amounts of alkene and diene isomers found in P. remota cuticle that are not found in workers from the natal nest. The data clearly show that the majority of the compounds present in P. droryana cuticle are endogenously produced, although a few unsaturated compounds are acquired from the environment, increasing the chemical differences and, consequently, the rejection percentages.

Generalized-positioning for mixed-frequency of mixed-GNSS and its preliminary applications

Modernized GPS and GLONASS, together with new GNSS systems, BeiDou and Galileo, offer code and phase ranging signals in three or more carriers. Traditionally, dual-frequency code and/or phase GPS measurements are linearly combined to eliminate effects of ionosphere delays in various positioning and analysis. This typical treatment method has imitations in processing signals at three or more frequencies from more than one system and can be hardly adapted itself to cope with the booming of various receivers with a broad variety of singles. In this contribution, a generalized-positioning model that the navigation system independent and the carrier number unrelated is promoted, which is suitable for both single- and multi-sites data processing. For the synchronization of different signals, uncalibrated signal delays (USD) are more generally defined to compensate the signal specific offsets in code and phase signals respectively. In addition, the ionospheric delays are included in the parameterization with an elaborate consideration. Based on the analysis of the algebraic structures, this generalized-positioning model is further refined with a set of proper constrains to regularize the datum deficiency of the observation equation system. With this new model, uncalibrated signal delays (USD) and ionospheric delays are derived for both GPS and BeiDou with a large dada set. Numerical results demonstrate that, with a limited number of stations, the uncalibrated code delays (UCD) are determinate to a precision of about 0.1 ns for GPS and 0.4 ns for BeiDou signals, while the uncalibrated phase delays (UPD) for L1 and L2 are generated with 37 stations evenly distributed in China for GPS with a consistency of about 0.3 cycle. Extra experiments concerning the performance of this novel model in point positioning with mixed-frequencies of mixed-constellations is analyzed, in which the USD parameters are fixed with our generated values. The results are evaluated in terms of both positioning accuracy and convergence time.