577 research outputs found
Spectral feature classification of oceanographic processes using an autonomous underwater vehicle
Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution June 2000The thesis develops and demonstrates methods of classifying ocean processes using
an underwater moving platform such as an Autonomous Underwater Vehicle (AUV).
The "mingled spectrum principle" is established which concisely relates observations
from a moving platform to the frequency-wavenumber spectrum of the ocean process.
It clearly reveals the role of the AUV speed in mingling temporal and spatial
information. For classifying different processes, an AUV is not only able to jointly
utilize the time-space information, but also at a tunable proportion by adjusting
its cruise speed. In this respect, AUVs are advantageous compared with traditional
oceanographic platforms.
Based on the mingled spectrum principle, a parametric tool for designing an AUVbased
spectral classifier is developed. An AUV's controllable speed tunes the separability
between the mingled spectra of different processes. This property is the key to
optimizing the classifier's performance.
As a case study, AUV-based classification is applied to distinguish ocean convection
from internal waves. The mingled spectrum templates are derived from the MIT
Ocean Convection Model and the Garrett-Munk internal wave spectrum model. To
allow for mismatch between modeled templates and real measurements, the AUVbased
classifier is designed to be robust to parameter uncertainties. By simulation
tests on the classifier, it is demonstrated that at a higher AUV speed, convection's
distinct spatial feature is highlighted to the advantage of classification.
Experimental data are used to test the AUV-based classifier. An AUV-borne flow
measurement system is designed and built, using an Acoustic Doppler Velocimeter
(ADV). The system is calibrated in a high-precision tow tank. In February 1998, the
AUV acquired field data of flow velocity in the Labrador Sea Convection Experiment.
The Earth-referenced vertical flow velocity is extracted from the raw measurements.
The classification test result detects convection's occurrence, a finding supported by
more traditional oceanographic analyses and observations. The thesis work provides
an important foundation for future work in autonomous detection and sampling of
oceanographic processes.This thesis research
has been funded by the Office of Naval Research (ONR) under Grants NOOOl4-95-1-1316,
NOO0l4-97-1-0470, and by the MIT Sea Grant College Program under Grant NA46RG0434
Keyword Targeting Optimization in Sponsored Search Advertising: Combining Selection and Matching
In sponsored search advertising (SSA), advertisers need to select keywords
and determine matching types for selected keywords simultaneously, i.e.,
keyword targeting. An optimal keyword targeting strategy guarantees reaching
the right population effectively. This paper aims to address the keyword
targeting problem, which is a challenging task because of the incomplete
information of historical advertising performance indices and the high
uncertainty in SSA environments. First, we construct a data distribution
estimation model and apply a Markov Chain Monte Carlo method to make inference
about unobserved indices (i.e., impression and click-through rate) over three
keyword matching types (i.e., broad, phrase and exact). Second, we formulate a
stochastic keyword targeting model (BB-KSM) combining operations of keyword
selection and keyword matching to maximize the expected profit under the chance
constraint of the budget, and develop a branch-and-bound algorithm
incorporating a stochastic simulation process for our keyword targeting model.
Finally, based on a realworld dataset collected from field reports and logs of
past SSA campaigns, computational experiments are conducted to evaluate the
performance of our keyword targeting strategy. Experimental results show that,
(a) BB-KSM outperforms seven baselines in terms of profit; (b) BB-KSM shows its
superiority as the budget increases, especially in situations with more
keywords and keyword combinations; (c) the proposed data distribution
estimation approach can effectively address the problem of incomplete
performance indices over the three matching types and in turn significantly
promotes the performance of keyword targeting decisions. This research makes
important contributions to the SSA literature and the results offer critical
insights into keyword management for SSA advertisers.Comment: 38 pages, 4 figures, 5 table
Genome factor and gene pleiotropy hypotheses in protein evolution
<p>Abstract</p> <p/> <p>The debate of genomic correlations between sequence conservation, protein connectivity, gene essentiality and gene expression, has generated a number of new hypotheses that are challenging the classical framework of molecular evolution. For instance, the translational selection hypothesis claims that the determination of the rate of protein evolution is the protein stability to avoid the misfolding toxicity. In this short article, we propose that gene pleiotropy, the capacity for affecting multiple phenotypes, may play a vital role in molecular evolution. We discuss several approaches to testing this hypothesis.</p> <p>Reviewers</p> <p>This article was reviewed by Dr Eugene Koonin, Dr Arcady Mushegian and Dr Claus Wilke.</p
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