797 research outputs found
Hybrid Neural Networks for Frequency Estimation of Unevenly Sampled Data
In this paper we present a hybrid system composed by a neural network based
estimator system and genetic algorithms. It uses an unsupervised Hebbian
nonlinear neural algorithm to extract the principal components which, in turn,
are used by the MUSIC frequency estimator algorithm to extract the frequencies.
We generalize this method to avoid an interpolation preprocessing step and to
improve the performance by using a new stop criterion to avoid overfitting.
Furthermore, genetic algorithms are used to optimize the neural net weight
initialization. The experimental results are obtained comparing our methodology
with the others known in literature on a Cepheid star light curve.Comment: 5 pages, to appear in the proceedings of IJCNN 99, IEEE Press, 199
Arrhythmogenic right ventricular cardiomyopathy associated with severe left ventricular involvement in a cat.
An 8-year-old, 4 kg, intact female, domestic shorthaired cat was
referred for tachypnea and pleural effusion. A 24-h Holter recording showed
numerous polymorphic ventricular premature complexes with left and right bundle
branch block morphology. Echocardiographic examination revealed right atrial and
ventricular dilation. The right ventricular free wall was thin and aneurysmal. The
cat died 10 days after initiation of antiarrhythmic therapy. Gross and histopathological
findings were consistent with arrhythmogenic right ventricular cardiomyopathy
(ARVC) associated with severe left ventricular involvement
Production and production over-supply in construction: estimating unsold stock in Italy
PurposeThe aim of the article is to identify the limitations and critical issues in the way information in the real estate sector in Italy is currently managed, and propose the principles of a method that would provide information and comparison of the phenomenon of over-supply and non-rational land use. This study is based on a series of assumptions, the first of which is a definition of ???unsold???, deemed to mean ???the amount of new housing units neither occupied nor sold nor rented???. In effect, unsold stock can be considered as over-supply of construction.
Design/methodology/approachThe article identifies the critical aspects in the determination of unsold real estate in Italy, starting from the available data and research already carried out; the results are often contradictory. The comparison with programming systems of building production adopted in other countries allows identification of the guidelines can be used to better understand and combat the phenomenon.
FindingsThe assessment of the state of the art provides a clear picture of the shortcomings and potential of the tools used to date to meet the need of studying a complex phenomenon with many obscure points. Following the empirical analysis comes out a picture of inefficiencies due to the poor quality of 'information as well as the reluctance of data sharing and integration procedures by the institutional and market players.
Research limitations/implicationsThe research produces solutions addressed to the Italian situation, but it identifies systems and methods used in other countries.
Practical implicationsThe article suggests the collection systems and management information that can be used for a more accurate knowledge of unsold real estate.
Originality/valueThe article seeks to provide the necessary answers to those who must understand the reasons of harmful effects for the market, such as overproduction; besides some models focused on three areas - the procedures, the organization, the market - are also proposed
The Convergence of Schenkerian Music Theory and Generative Linguistics: An Analysis and Composition
This thesis engages a purported connection between Schenkerian music theory and the Minimalist Program within generative linguistics both scientifically and creatively. The first chapter expounds the link between Schenkerian theory and the Minimalist Program which has been recently substantiated in a doctoral dissertation by Somangshu Mukherji at Princeton University and details the methodological framework for investigating musical structures within this paradigm. Chapter two presents three case studies including the opening phrase of Mozart’s K. 332 Mvt. 1 piano sonata, and the tunes “Georgia on My Mind” and “Blue Bossa” in order to exemplify the aforementioned methodology and provide scientific evidence affirming this generative framework. Chapter three concludes with a creative investigation of the theoretical ideas which this thesis engages and consists of a string quartet that draws upon the notions of music and language, and music as derived from a computational system
A note on some mathematical models on the effects of Bt-maize exposure
Some mathematical models for the estimation of the effects of Cry1Ab and
Cry1F Bt-maize exposure in the biodiversity are discussed. Novel results about
these models are obtained and described in the note. The exact formula for the
proportion of the population that suffers mortality exposed to Cry1Ab pollen,
underlining its dependence on the margin from the Bt crop edge, is derived. In
addition, regarding Cry1F pollen effects, it is proposed a procedure, using a
probabilistic and statistical approach, that computes the width of the non
Bt-stripes used as mitigation measures. Finally, it has been derived a lower
bound, using probabilistic consideration, on the species sensitivity of
Lepidoptera.Comment: 10 pages, 1 figure. Early draft of a paper accepted for publication
on Environmental and Ecological Statistic
A novel scheme to detect optical DPSK signals
We propose and demonstrate a novel approach to
detect optical differential phase-shift keying signals. The technique is based on differential phase-to-polarization conversion in a polarization-maintaining fiber, so that the polarization-modulated signal can be detected by using a polarizer and a common intensity modulation receiver
Modelization and characterization of a CMOS camera as an optical real-time oscilloscope
Complementary Metal-Oxide Semiconductor (CMOS) camera sensors are embedded in many consumer electronics products: Thanks to the Rolling Shutter (RS) readout mode, they can detect a time-varying light intensity, which is the key to realize Optical Camera Communication (OCC). To this aim, we introduce here a model describing the camera as a Real-Time Oscilloscope (RTO) detecting optical signals; by means of this approach, we can now characterize the Complementary Metal-Oxide Semiconductor (CMOS) camera by means of parameters that correspond to common oscilloscope specifications, such as the frequency response, the noise, the Signal to Noise Ratio (SNR), the total harmonic distortion (THD), etc.; all of these are introduced and measured in terms of the camera parameters. This approach provides for the first time a set of quantitative tools that should be used to maximize the OCC transmission performance by allowing the optimal selection of the camera settings
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