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Topic: Scientific modeling

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	Scientific modelling - Wikipedia, the free encyclopedia
		Scientific modelling is the process of generating abstract or conceptual models.
		This may be due to differing requirements of the model's end users or to conceptual or esthetic differences by the modellers and decisions made during the modelling process.
		Esthetic considerations that may influence the structure of a model might be the modeller's preference for a reduced ontology, preferences regarding probabilistic models vis-a-vis deterministic ones, discrete vs continuous time etc. For this reason users of a model need to understand the model's original purpose and the assumptions of its validity.
	en.wikipedia.org /wiki/Scientific_modeling (334 words)

	Chapter 1: Introduction: What is Scientific Inquiry?
		One reason that a model is always simpler than the actual phenomenon observed is that scientific theories, laws and models are in fact simplifications and generalizations of the patterns observed in nature.
		In this case, once your model for the cause of a rainbow is acceptable, you will be able to use it to tell someone the conditions of the sky and where to stand and in what orientation in order to see a rainbow.
		The foundations of scientific inquiry in the physical sciences rest on developing the skills to pose a scientific question, to develop, to test and to apply a scientific model that adequately accounts for the observed phenomena.
	acept.la.asu.edu /courses/phs110/si/chapter1/main.html (2775 words)

	CITE Journal -- Volume 2, Issue 4
		The role played by scientific models is an often under-emphasized aspect of the conduct of science associated with an understanding of the nature of science and scientific inquiry.
		Models as pedagogical tools appeared to characterize the prospective science teachers' initial conceptions of scientific models even when some of the questions designed to elicit their understanding of how models are built and used by scientists were examined.
		Their recognition of the power of models to enhance learning of established scientific ideas is not inaccurate Yet, we had hoped that by engaging them in modeling activities we might expand their understanding to include an appreciation of the importance of models in the scientific endeavor.
	www.citejournal.org /vol2/iss4/science/article1.cfm (5271 words)

	Modeling & Computer Science
		Modeling is a method which develops mathematical representations of objects, systems or processes (molecules, electronic components, industrial processes, software etc...) to study or optimize them.
		Several types of models and techniques of modeling can be used: for example, creating objects in 2 or 3 dimensions.
		Modeling and scientific computing are computing tools which provide quick and reliable solutions to real life problems as most parameters and hypotheses can be analyzed.
	istil.univ-lyon1.fr /english/mcs.html (882 words)

	[No title] (Site not responding. Last check: 2007-11-06)
		The National Science Education Standards and Benchmarks to scientific literacy have served to emphasize the centrality of scientific modeling by recognizing it as one of several unifying themes of science.
		From a modeling perspective, it would be ideal to use an open-ended modeling software such as Stagecast creator with student teachers so that they could use such a tool for building their own models or for engaging their own students to build models.
		Modeling tools and approaches could also be incorporated in other teacher education courses such as science courses and methods courses, so that student teachers have more time and opportunities to struggle with the sometimes-complicated pedagogical and epistemic ideas that using these tools can raise.
	punya.educ.msu.edu /PunyaWeb/COD/chapters/christinaschwartz.1.doc (3762 words)

	Teaching Numerical Modeling in the Environmental Sciences
		The loose coupling of GIS and off-the-shelf models may be ideal for many environmental scientists working in advisory or dedicated research institutes but it poses several problems for those wishing to experiment with modeling, or to teach it to university and post-academic students.
		Model animations have been shown to be very useful for illustrating processes that are too slow or imperceptible to experience in the field, e.g.
		A disadvantage of students constructing their own models is that they may use concepts and methods that may be inappropriate, but this can be prevented by good support from the tutor.
	www.colorado.edu /research/cires/banff/pubpapers/251/index.html (3431 words)

	Scientific Modeling & Viz Classroom - Planning Document
		The purpose of this document is to describe plans for a scientific modeling and visualization classroom at Virginia Tech.
		Scientific visualization is an area rich with interesting and relatively accessible research opportunities for undergraduates.
		ESM 5984 Scientific Visual Data Analysis and Multimedia.
	www.sv.vt.edu /future/vizclass.html (3363 words)

	Modeling Introduction
		Modeling Theory aims at elucidating the roles of models and modeling in scientific knowledge and practice.
		Modeling pedagogy and its implementation in physics teaching is addressed at the Modeling Instruction Program site.
		The program is grounded in a theory of instruction which is centrally concerned with the construction, validation and use of scientific models for objects and processes in the real world.
	modelingnts.la.asu.edu /html/Modeling.html (379 words)

	Technology Opportunity: Scientists' Intelligent Graphical Modeling Assistant (SIGMA) (Site not responding. Last check: 2007-11-06)
		The model itself is represented as a data dependency graph that illustrates how each derived model parameter is calculated from input parameters via a series of application equations.
		Similarly, sharing of model fragments becomes more feasible when the scientific content of those fragments is readily understood and their modeling assumptions are clearly identified.
		Conventional scientific modeling can be extremely labor intensive, and staffing in scientific labs is often insufficient to provide for extensive programming assistance to accomplish the necessary work in a reasonable timeframe.
	ic-www.arc.nasa.gov /projects/sigma/sigma-tech-opp.html (851 words)

	Modeling Lesson
		More than one type of model can be used to study the same complex system, each model shedding light on some different aspect of the complex system but each model has limitations on what kind of information it can give you.
		Models are created to answer specific questions, how you design your model depends on the question(s) you want it to answer.
		A previous model of gases, ''The Kinetic theory of gases'', had made a number of accurate predictions about a gases physical and chemical behavior, by modeling a gas as a mass of moving, colliding particles.
	www.nas.nasa.gov /About/Education/Ozone/modeling.html (1958 words)

	SOFTWARE INFRASTRUCTURE FOR SUPPORT OF SCIENTIFIC MODELING
		The model was parallelized and the horizontal differencing was generalized to accommodate arbitrary horizontal coordinates.
		In conjunction with the Bombay release, an FMS workshop was held at GFDL to familiarize the laboratory with the capabilities of FMS.
		Representatives from nearly a dozen outside modeling institutions were invited to attend the workshop as observers, and participated in an afternoon session discussing possible ways in which GFDL could interact with the outside world using FMS.
	www.gfdl.noaa.gov /reference/AR00/1FMS.html (2485 words)

	SIGMA Introduction (Site not responding. Last check: 2007-11-06)
		Unfortunately, scientific models can be difficult and time-consuming to implement, and there is little software engineering support specifically available for constructing scientific models.
		Using extensive semantic knowledge about the scientific domain and the modeling equations, the system automatically fills in missing details of the model specification and ensures that the model being built is consistent and coherent.
		The primary contribution we make with our tool is to extend the notion of a scientific model beyond simply a set of equations, so that it includes a description of the underlying "modeling scenario".
	ic-www.arc.nasa.gov /projects/sigma/intro.html (476 words)

	Scientific Marketing: Modeling and Optimization for Strategic Promotions
		Typically, it is not possible to generate consistent models that describe each customer's utility and behavior, however, such information may still exist at an aggregate level.
		Once the customers' utility and behavior is understood, a model of how the customers' utility and behavior may change with respect to a new offer /promotion needs to be developed.
		For each specific new offer template, a model can be hypothesized that describes this change, and based on this model, the different parameters of such templates can be optimized.
	web.mit.edu /mitpep/pi/courses/scientific_marketing.html (1298 words)

	Biology - Modeling
		Since viruses can only be seen by powerful microscopes, this scientific visualization modeling experiment is to acquaint students in recognizing the various shapes and life cycles of viruses through the process of making both a simple physical model and a virtual model of a virus type on the computer.
		The physical model will be used to demonstrate the major parts of a virus and the computer model will be used to actually model all components of the virus.
		To further aid the students in starting the modeling process, have students begin their models by using primitive shapes (3D) that directly reflect the basic structure of the virus they are to model.
	www.ncsu.edu /scivis/biology.html (1178 words)

	Stochastic Modeling of Scientific Data
		Stochastic Modeling of Scientific Data combines stochastic modeling and statistical inference in a variety of standard and less common models, such as point processes, Markov random fields and hidden Markov models in a clear, thoughtful and succinct manner.
		The distinguishing feature of this work is that, in addition to probability theory, it contains statistical aspects of model fitting and a variety of data sets that are either analyzed in the text or used as exercises.
		Markov chain Monte Carlo methods are introduced for evaluating likelihoods in complicated models and the forward backward algorithm for analyzing hidden Markov models is presented.
	www.ramex.com /ch/ch-2332.html (190 words)

	Models as Languages: How Can Scientific Modeling Improve Environmental Policy Process? (Site not responding. Last check: 2007-11-06)
		While scientific models are often thought of as "descriptive" and as mainly designed to generate predictions, in fact scientific models can be constructed for many and varied purposes.
		One key--and growing--use of models is to improve communication among stakeholders in contentious and public environmental management processes.
		It will be argued that the development of useful "demand" models will require a significant re-thinking of the criteria by which we form and judge scientific models.
	oregonstate.edu /Dept/IIFET/2000/abstracts/norton.html (247 words)

	Environmental Research Scientist - 3020
		Under general supervision, an employee in this class is responsible for development and analysis of scientific research projects dealing with pollution control issues, and for providing expert scientific and technical advice to staff of the Pollution Control Agency.
		Position is involved in scientific modeling and other research work designed to test specific hypotheses or to make observations within a specific environmental field.
		Scientific, experimental, and research techniques sufficient to conduct extensive and sophisticated scientific research and analysis.
	www.doer.state.mn.us /stfcs-ac/cspcs-e/e-3020.htm (327 words)

	Computer Science Research at Almaden - Data Compression & Scientific Modeling
		For superior compression, the secret is in the modeling (and visa versa!!) We've pushed back the frontiers of applied information theory with the invention of general-purpose and adaptive arithmetic coding for compression.
		Its introduction of adaptivity also drastically reduced the numbers of compression models to be invented for related applications, introducing the robustness to cover large variations in data.
		With the discovery of a duality between the mathematics of information theory and statistical modeling, the Minimum Description Length principle and Stochastic Complexity concepts were invented to avoid the overfitting of data.
	www.almaden.ibm.com /cs/compression (356 words)

	Principles and philosophy of modeling in biomedical research -- Massoud et al. 12 (3): 275 -- The FASEB Journal
		role of models and modeling is often controversial and ill understood.
		The purpose of experimental modeling according to Yates (4, 6) and White et al.
		models and is an extremely useful analytic device (11).
	www.fasebj.org /cgi/content/full/12/3/275 (6615 words)

	CRLT - SMIT'N (Site not responding. Last check: 2007-11-06)
		We explored various modeling activities, scientific inquiry, nature of science, science process skills, and biology content, through the overarching theme of scientific modeling.
		We also explored the new FOSS curriculum that was adopted by MCCSC, through the lens of inquiry, nature of science, and scientific modeling.
		Data analysis from the first summer indicates that teachers made growth in their understandings of the target goals, but of course, more work needs to be done.
	cee.indiana.edu /research/smitn.html (211 words)

	Physical Modeling of Scientific Instruments
		The success of physical models in the analysis of observational data with strong instrumental signatures is shown, and a concept for model based calibration developed.
		Had the FOS model been available early on, it would certainly have influenced the specifications for the pipeline, and even earlier the introduction of solar blind detectors.
		On the other hand, a model designed to completely cope with the analysis of long slit echelle spectra must be able to predict the geometrical pattern (curvature of orders, of slit images and field distortions), and the blazed sensitivity variations in dispersion direction as well as the spatial intensity profiles (LSF and interorder background).
	www.cv.nrao.edu /adass/adassVI/rosam.html (1455 words)

	se_tsmith
		Many areas of scientific and engineering research require comprehensive and integrated computational support for the development, evaluation and application of symbolic models of phenomena.
		The modeling environment of a CMS is based on a characterization of scientific modeling activities that is focussed on the manner in which scientific concepts are represented, manipulated, and evaluated in the scientific modeling process.
		A simple GUI based on a visual representation of CML supports the easy construction and manipulation of scientific modeling concepts in general and of the concept of a ``model'' in particular and provides access to the modeling environment of the CMS.
	nssdc.gsfc.nasa.gov /sisic/abstracts/se_tsmith.html (614 words)

	Press Release : Benchmarks of Scientific Modeling Software Reveal That FEMLAB Rivals Specialized Packages
		The FEMLAB 3.0a benchmark evaluation was conducted by two independent research groups-The Parallel and Scientific Computing Institute at The Royal Institute of Technology (Stockholm, Sweden) and the Centre for Mathematical Sciences at the Lund Institute of Technology (Lund, Sweden).
		Fluid-dynamics capabilities of FEMLAB and Fluent were tested using classic models from the scientific literature.
		A particular strength of the package is its PDE modeling capability, enabling equations from various fields such as structural mechanics, electromagnetics, fluid flow, and chemistry to be linked and solved all in the same model and all at the same time.
	www.comsol.com /press/pr/040430.php (931 words)

	A Message from the Program Director
		The program, which began in the fall 1995 semester, is designed to provide a broad yet rigorous training in areas related to scientific computing, including modern computing tools and methods, and numerical and mathematical analysis as arises in various applications.
		Scientific computing is an indispensable part of almost all scientific investigation and technological development at universities, government laboratories, and within the private sector.
		Typically a scientific computing team consists of several people trained in some branch of mathematics, science, or engineering.
	www.math.nyu.edu /degree/scicomp.html (1698 words)

	Micromath Research - Scientific Curve Fitting (Nonlinear Regression), Data Analysis, Statistics and Graphing Software
		The Scientist Diffusion Library is a collection of linear models, expressed as Laplace Transforms, for simulating and analyzing diffusion and heat conduction.
		Scientist is required to use the models in the Diffusion Library.
		The models include bolus input, constant rate IV input; first order or Michaelis-Menton output and both single and multiple dose models.
	www.micromath.com (602 words)

	STA 376: Advanced Modeling and Scientific Computing (Site not responding. Last check: 2007-11-06)
		An introduction to advanced statistical modeling and modern numerical methods useful in implementing statistical procedures for data analysis, model exploration, inference, and prediction.
		Methods are applied to substantial problems in discrete multivariate analysis, time series, econometrics, non-linear regression models, density estimation, applications with censored and missing data, hierarchical models, mixture modeling, and non-linear regressions.
		Some experience in a lower level programming language such as C or FORTRAN and a familiarity with UNIX workstations is assumed; experience with a high level language such as S-Plus or Matlab is useful, but not required.
	www.isds.duke.edu /courses/Spring04/sta376 (153 words)

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