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Posts Tagged ‘math modeling’

SIAM News: May Issue Now Available

The May issue of SIAM News‬ is now officially available online! Learn more about mathematical models for fighting Zika Virus‬, mathematical matchmaking, the new national Guidelines for Assessment and Instruction in Mathematical Modeling Education (GAIMME), a new method for emotional interpretation based on nonlinear time series analysis and many other interesting topics:

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Predict the Future … With Math!

art2_150x197As Math Awareness Month (MAM) winds down, we wanted to leave you with another post! The goal of MAM is to increase public understanding and appreciation for mathematics. This year’s theme is “The Future of Prediction”. Many may not realize that mathematics and statistics are widely used to predict a number of things, such as, the outcome of a ball game, the results of elections, U.S industrial production of oil and natural gas prices, and even your health. Joe Kincaid, Senior Business Process Engineer of Blue Cross and Blue Shield, determined that the healthcare industry could forecast the likelihood of coronary heart disease through the use of mathematics, statistics, and technology advancements, which he discusses in his essay “To your Health”. Read the rest of this entry »

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Math Predictions for 2016 MLB Winners

The start of April not only brings April showers and Math Awareness Month, it also brings…baseball season. Bruce Bukiet, New Jersey Institute of Technology (NJIT) Mathematical Sciences Professor and Associate Dean, is using mathematical statistics to predict the winners of the 2016 Major League Baseball season. And according to his math, the Mets win. 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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Modeling robust use of pesticides

Adaptive control techniques can help manage pests more effectively

nugget_iconAs population growth, greater food consumption, competition for land use, and climate change pose challenges to world food production, managing loss of crop due to pests and weeds becomes increasingly important. While chemical pesticides offer effective means for control, potential loss of crop yield  is still significant, as is cost. Global potential loss from pests has been estimated to be between 50% and 80% of yield based on crop type.

In a paper published last week in the SIAM Journal on Applied Mathematics, authors Chris Guiver et al propose adaptive control techniques to model pest dynamics and management as a control system. Read the rest of this entry »

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SIAM News: January/February Issue Now Available

The latest issue of SIAM News is now available online! Mathematics not only enhances scientific progress, but also hides within simple gestures we instinctively repeat every day. Such is the case when we turn on the lights. What does it take to ensure that every time we enter a dark room and flip the light switch, electricity is available and waiting for us to use? Read more about optimization and how one can generate electricity in a manner that is both satisfactory for consumers and efficient from the network point of view in the most recent issue of SIAM News.

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The mathematics of electricity costs [Video]

In this video from the 2013 SIAM Annual Meeting, Alejandro Jofré of Universidad de Chile considers a wholesale electricity market model with generators interacting strategically and general networks including externalities such as transmission losses. Previous work shows how mechanisms such as the case when prices correspond to the Lagrange multipliers of a centralized cost minimization program allow the producers to charge significantly more than marginal price. This situation originates an important regulatory problem. In this presentation we consider an incomplete information setting where the cost structure of a producer is unknown to both its competitor and the regulator. We derive an optimal regulation mechanism and compare its performance to the “price equal to Lagrange multiplier”. Watch the video:

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Jamology – the mathematics of traffic jams [Video]

Jamming phenomena are seen in various transportation system including cars, buses, pedestrians, ants and molecular motors, which are considered as “self-driven particles”. This interdisciplinary research on jamming of self-driven particles has been recently termed “jamology”. This is based on mathematical physics and includes engineering applications as well. In his talk at the 2013 SIAM Annual Meeting, Katsuhiro Nishinari of the University of Tokyo traced the background of this research: simple mathematical models, such as the asymmetric simple exclusion process and the Burgers equation, were introduced as the basis of all kinds of traffic flow. This was then extended in order to account for various traffic phenomena, and the comparison between theory and experiment was given to show that the models are able to capture fundamental features of observations. Watch the video!

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The mathematics of conservation decision making [Video]

Species are currently becoming extinct at least 100 times the background rate. The resources available to save biodiversity are inadequate. Consequently we need to optimise the return on investment from conservation decisions. In this talk at the 2013 SIAM Annual Meeting, Hugh Possingham of the University of Queensland showed how optimization tools are being used to solve conservation problems such as reserve system design, and allocating funds to threatened species management. Watch the video!

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Big Data and mathematical modeling [Video]

At the SIAM Conference on Computational Science and Engineering held in Boston in February 2013, professional mathematicians from various fields discussed the significance of big data and the importance of mathematical modeling to make sense of and interpret all that data in various fields from social networks and epidemiology to climatology. Watch a brief video with highlights!

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