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Posts Tagged ‘SIAM Journals’

Segmenting Ultrasound Video with a Wavelet Variational Model

Image segmentation, the process of separating a digital image into multiple sections for individual examination, is frequently used in medical image analysis. For example, segmentation in ultrasound footage helps identify boundaries and regions of interest (ROI) that facilitate image interpretation. Efficient segmentation of ultrasound videos, however, is often complicated by low contrast, shadow effects, and complex “noise” statistics (unexplained variations). In addition, real-time applications such as navigation during operational surgery require efficient algorithms.

In an article published this month in the SIAM Journal on Imaging Sciences, authors Jiulong Liu, Xiaoqun Zhang, Bin Dong, Zuowei Shen, and Lixu Gu propose a video segmentation model to recognize ROI in ultrasounds. Read the rest of this entry »

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Applying Parameter Selection and Verification Techniques to an HIV Model

Physical and biological models often have hundreds of inputs, many of which may have a negligible effect on a model’s response. Establishing parameters that can be fixed at nominal values without significantly affecting model outputs is often difficult; sometimes these parameters cannot be simply discerned by the outputs. Thus, verifying that a parameter is noninfluential is both computationally challenging and quite expensive. Read the rest of this entry »

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Q&A: Tamara Kolda on SIAM Journal Macro Update

In January, SIAM introduced a substantially updated macro set for 11 of our journals, with a corresponding upgrade to our four exclusively online journals to follow. This development was the work of a committee under the leadership of Tamara G. Kolda of Sandia National Laboratories. We sat down with Tammy to find out what the update will mean for SIAM journal authors and readers. Read the rest of this entry »

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SIAM Manuscripts Enhanced Due to Modernized Macros

Last month, SIAM released a significantly modernized set of LaTeX2e Macro files for use with 11 of our journals. A corresponding upgrade to macros for our four (soon to be five) exclusively online journals will follow. Read the rest of this entry »

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Nugget: Improving Electric Motor Efficiency Via Shape Optimization

Philadelphia, PA – In our competitive global society, successful and economical design of automotive and industrial structures is crucial. Optimizing the geometry of individual pieces of complex machines improves performance and efficiency of the entire device.

To achieve this, the automotive and aeronautic industries often rely on shape optimization, an approach that uses modeling to create a framework for making devices as smooth and efficient as possible. “A smoother rotation of the rotor can increase the energy efficiency of the motor, and at the same time reduce unwanted side effects like noise and vibrations,” says mathematician Ulrich Langer. Read the rest of this entry »

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Supplementary Materials for SIAM journals

SIAM journals have entered a new era and are now considering unrefereed supplementary materials for publication along with the author’s manuscript. The first journals to seize the opportunity, SIAM Journal on Matrix Analysis and Applications, SIAM Journal on Scientific Computing and SIAM Review, began taking submissions with accompanying supplemental files in January.  SIAM Journal on Mathematical Analysis is next in line, with other journals expected to follow.

Prior to this new initiative, SIAM Journal on Applied Dynamical Systems and SIAM Journal on Imaging Sciences did review refereed supplemental content. SIAM journals that consider supplemental content for publication under the new policy will treat it on an unrefereed basis.

Supplementary materials must be submitted at the same time the article is first submitted. They might include additional figures or examples, animations, data sets used in the paper, computer code used to generate figures or tables, or other materials that are necessary to fully document the research contained in the paper or to facilitate the readers’ ability to understand and extend the work.

Supplementary materials, though not refereed, will be available to referees. The referees will be asked to give the materials at least a cursory look and verify that they are appropriate to accompany the paper. The referees or editor may suggest changes.

If published, they will be linked from the main article webpage and will be clearly marked as unrefereed supplementary materials associated with a particular paper.


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A math-based model for deep-water oil drilling

Oil well control is one of the most important processes during drilling operations. In deepwater drilling, controlling pressure in the oil well is crucial, as excessive pressures in the drilled hole can result in blowouts, leading to disastrous events like the 2010 Gulf of Mexico Oil Spill.

The deeper the well, the higher the pressure, and the higher the risks associated with tapping oil from wells. During drilling, when the pressure applied to balance the hydrocarbon pressure in a well is not great enough to overcome that exerted by gas and fluids in the rock formation drilled, water, gas, oil, or other formation fluid can enter the hole. This is called a “gas kick,” which in worst-case scenarios can lead to blowouts.

In a paper published earlier this month in the SIAM Journal on Mathematical Analysis, author Steinar Evje presents new analysis of a mathematical model that has applications to the study of such gas kicks in deep-water oil wells. Read the rest of this entry »

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SIAM Journal on Imaging Sciences paper selected as New Hot Paper

Highly-cited research on algorithms for medical imaging, intelligence surveillance and data mining

According to Thomson Reuters Essential Science Indicators, the article, “The Split Bregman Method for L1-Regularized Problems” published in SIAM Journal on Imaging Sciences is a “New Hot Paper” in the field of computer science. The paper, which appears in Volume 2 (2), pp 323-343, 2009, of the journal highlights cutting-edge numerical algorithms for the solution of problems related to recovery and restoration of signals, images, and video from meager data.

This designation means that the paper is one of the most highly-cited articles in this discipline published over the last two years. Authors Tom Goldstein and Stanley Osher attribute the high citation of their research to the simplicity and speed of the algorithms they propose as well as its wide-ranging potential applications. “[The paper] gives state-of-the-art, fast, simple, and versatile numerical algorithms for solving a class of problems of great practical and theoretical significance,” the authors said in an e-mail.

The research has relevance in various areas such as medical imaging, intelligence surveillance, statistics, and data mining. “This is a method which is useful in predicting what movies Netflix customers might prefer, finding objects on the ground from satellite observations, enabling patients to spend less time in MRI machines, reducing radiation exposure from CT scans, allowing doctors to track needles in ultrasound machines, and more,” the authors wrote.

New challenges and future directions include figuring out ways to further speed up methods based on these algorithms, optimizing geometries, enabling imaging capabilities through turbulence, and enhancing filtering methods for dynamical systems.

Goldstein is a postdoctoral research fellow in the Department of Electrical Engineering at Stanford University and Osher is a professor of mathematics, computer science, and electrical engineering at the University of California at Los Angeles.

“Hot papers” are papers published within the previous two years that receive an unusually high number of citations in the latest two-month period, according to data from Thomson Reuters Essential Science Indicators.

Access the complete paper here.

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Mathematically ranking ranking methods

In a world where everything from placement in a Google search result to World Cup eligibility depends on ranking and numerical ratings of some kind, it is becoming increasingly important to analyze the algorithms and techniques that underlie such ranking methods in order to ensure fairness, eliminate bias, and tailor them to specific applications.

In a paper published this month in the SIAM Journal on Scientific Computing, authors Timothy Chartier, Erich Kreutzer, Amy Langville, and Kathryn Pedings mathematically analyze three commonly-used ranking methods.  “We studied the sensitivity and stability of three popular ranking methods: PageRank, which is the method Google has used to rank web pages, and the Colley and Massey methods, which have been used by the Bowl Championship Series to rank U.S. college football teams,” explains Langville. Read the rest of this entry »

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Migratory Birds, domestic poultry and avian influenza

The persistence and recurrence of H5N1 avian influenza in endemic regions can largely be blamed on movement and infection by migratory birds. Trade in poultry, poultry products and caged birds, and movement of wild birds also account for H5N1 prevalence in these areas. Several recent outbreaks of avian influenza have suggested strong evidence of migratory birds playing a role in transmitting the virus over long distances.

In a paper published last week in the SIAM Journal on Applied Mathematics, authors Lydia Bourouiba, Stephen A. Gourley, Rongsong Liu, and Jianhong Wu analyze the interaction between non-migratory poultry and migratory birds in order to investigate the role of the latter in the spread of H5N1. Read the rest of this entry »

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