Explanatory power Explanatory power is the ability of a hypothesis to effectively explain the subject matter it pertains to. One theory is sometimes said to have more explanatory power than another theory about the same subject matter if it offers greater predictive power. That is, if it offers more details about what we should expect to see, and what we should not. Explanatory power may also suggest that more details of causal relations are provided, or that more facts are accounted for. Scientist David Deutsch adds that a good theory is not just predictive and falsifiable (i.e. testable); a good explanation also provides specific details which fit together so tightly that it is difficult to change one detail without affecting the whole theory. The opposite of explanatory power is explanatory impotence. Overview[edit] Deutsch says that the truth consists of detailed and "hard to vary assertions about reality" Deutsch takes examples from Greek mythology. References[edit]
Complexity The complexity of a physical system or a dynamical process expresses the degree to which components engage in organized structured interactions. High complexity is achieved in systems that exhibit a mixture of order and disorder (randomness and regularity) and that have a high capacity to generate emergent phenomena. Complexity across Scientific Disciplines Despite the importance and ubiquity of the concept of complexity in modern science and society, no general and widely accepted means of measuring the complexity of a physical object, system, or process currently exists. The lack of any general measure may reflect the nascent stage of our understanding of complex systems, which still lacks a general unified framework that cuts across all natural and social sciences. While a general measure has remained elusive until now, there is a broad spectrum of measures of complexity that apply to specific types of systems or problem domains. General Features of Complexity Components. Emergence.
Theory choice A main problem in the philosophy of science in the early 20th century, and under the impact of the new and controversial theories of relativity and quantum physics, came to involve how scientists should choose between competing theories. The classical answer would be to select the theory which was best verified, against which Karl Popper argued that competing theories should be subjected to comparative tests and the one chosen which survived the tests. If two theories could not, for practical reasons, be tested one should prefer the one with the highest degree of empirical content, said Popper in The Logic of Scientific Discovery. Mathematician and physicist Henri Poincaré instead, like many others, proposed simplicity as a criterion.[1] One should choose the mathematically simplest or most elegant approach. Popper's solution was subsequently criticized by Thomas S.
Thinking Enterprise Competition Competition in sports. A selection of images showing some of the sporting events that are classed as athletics competitions. Consequences[edit] Competition can have both beneficial and detrimental effects. Many evolutionary biologists view inter-species and intra-species competition as the driving force of adaptation, and ultimately of evolution. Biology and ecology[edit] Economics and business[edit] Merriam-Webster defines competition in business as "the effort of two or more parties acting independently to secure the business of a third party by offering the most favorable terms".[4] It was described by Adam Smith in The Wealth of Nations (1776) and later economists as allocating productive resources to their most highly-valued uses.[5] and encouraging efficiency. Experts have also questioned the constructiveness of competition in profitability. Three levels of economic competition have been classified: Competition does not necessarily have to be between companies. Interstate[edit]
Simple animation 1, aircraft radial engine 2, oval Regulation 3, sewing machines 4, Malta Cross movement - second hand movement used to control the clock 5, auto change file mechanism 6, auto constant velocity universal joint 6.gif 7, gun ammunition loading system 8 rotary engine - an internal combustion engine, the heat rather than the piston movement into rotary movement # Via World Of Technology. 1, inline engine - it's cylinders lined up side by side 2, V-type engine - cylinder arranged at an angle of two plane 3, boxer engine - cylinder engine arranged in two planes relative
Occam's razor The sun, moon and other solar system planets can be described as revolving around the Earth. However that explanation's ideological and complex assumptions are completely unfounded compared to the modern consensus that all solar system planets revolve around the Sun. Ockham's razor (also written as Occam's razor and in Latin lex parsimoniae) is a principle of parsimony, economy, or succinctness used in problem-solving devised by William of Ockham (c. 1287 - 1347). It states that among competing hypotheses, the one with the fewest assumptions should be selected. Other, more complicated solutions may ultimately prove correct, but—in the absence of certainty—the fewer assumptions that are made, the better. Solomonoff's theory of inductive inference is a mathematically formalized Occam's Razor:[2][3][4][5][6][7] shorter computable theories have more weight when calculating the probability of the next observation, using all computable theories which perfectly describe previous observations.
Living Code: The importance of visual programming Python has a well-earned reputation for being easy to use and to learn, at least for people who have learned programming in other languages first. Lately my kids have been very interested in programming, and I've found that Python doesn't come as easily to 6-11 year olds as it does to adult programmers. So I see two approaches to this problem, if it is a problem. One, let them use other languages than Python. Two, find (or make) ways for Python to be more approachable. Let's look at both of these. Scratch For languages other than Python, there are some really good choices. Learn more about this project Scratch is great for learning and for sharing. One option that is often suggested as a step up from Scratch is GameMaker, which apparently is a very nice commercial system that lets kids build games. Quartz Composer Another interesting system we've been playing around with lately is Quartz Composer. eToys One more tool we've begun to explore is Squeak/eToys. . Turtles Turning now to Python.
Reproducibility Aristotle′s conception about the knowledge of the individual being considered unscientific is due to lack of the field of statistics in his time, so he could not appeal to statistical averaging of the individual. History[edit] Boyle's air pump was, in terms of the 17th Century, a complicated and expensive scientific apparatus, making reproducibility of results difficult The first to stress the importance of reproducibility in science was the Irish chemist Robert Boyle, in England in the 17th century. The air pump, which in the 17th century was a complicated and expensive apparatus to build, also led to one of the first documented disputes over the reproducibility of a particular scientific phenomenon. Reproducible data[edit] Reproducibility is one component of the precision of a measurement or test method. Reproducibility is determined from controlled interlaboratory test programs or a Measurement systems analysis.[6][7] Reproducible research[edit] Noteworthy irreproducible results[edit]
Instances of Fractal Evolution « Mindsoul’s Weblog When couple of years ago (Nov 2006) I experienced author and biologist Dr. Bruce Lipton‘s 2-day presentation in his seminar produced by Spirit 2000 in San Francisco, I was totally blown away by the depth of insight I got into how my biology, my health, and how my health at the cellular level, is in my complete control through my beliefs (both conscious and subconscious). But one new thing Bruce added at the end of his presentation was his talk about how patterns of life and evolution are similar to patterns of fractal geometry. Dr. Fractal Geometry Fractal geometry is derived by a recursive mathematical formulas, and incredible shapes were produced when computers were strong and fast enough to be able to execute these very computing-intensive formulas. Concept of Fractal Evolution is that evolution follows a similar pattern, meaning “pattern of the whole is seen in the parts of the whole” quoting from Dr. Digital Technology and Unified Field Theory Dr. Evolution of the Web Like this:
Cognitive map Overview[edit] Cognitive maps serve the construction and accumulation of spatial knowledge, allowing the "mind's eye" to visualize images in order to reduce cognitive load, enhance recall and learning of information. This type of spatial thinking can also be used as a metaphor for non-spatial tasks, where people performing non-spatial tasks involving memory and imaging use spatial knowledge to aid in processing the task.[6] The neural correlates of a cognitive map have been speculated to be the place cell system in the hippocampus[7] and the recently discovered grid cells in the entorhinal cortex.[8] Neurological basis[edit] Cognitive mapping is believed to largely be a function of the hippocampus. Numerous studies by O'Keefe have implicated the involvement of place cells. Parallel map theory[edit] Generation[edit] The cognitive map is generated from a number of sources, both from the visual system and elsewhere. History[edit] The idea of a cognitive map was first developed by Edward C.
Experiment Even very young children perform rudimentary experiments in order to learn about the world. An experiment is an orderly procedure carried out with the goal of verifying, refuting, or establishing the validity of a hypothesis. Controlled experiments provide insight into cause-and-effect by demonstrating what outcome occurs when a particular factor is manipulated. A child may carry out basic experiments to understand the nature of gravity, while teams of scientists may take years of systematic investigation to advance the understanding of a phenomenon. Overview[edit] In the scientific method, an experiment is an empirical method that arbitrates between competing models or hypotheses.[1][2] Experimentation is also used to test existing theories or new hypotheses in order to support them or disprove them.[3][4] An experiment usually tests a hypothesis, which is an expectation about how a particular process or phenomenon works. History[edit] G. Types of experiment[edit] Natural experiments[edit]
Algorithm Flow chart of an algorithm (Euclid's algorithm) for calculating the greatest common divisor (g.c.d.) of two numbers a and b in locations named A and B. The algorithm proceeds by successive subtractions in two loops: IF the test B ≥ A yields "yes" (or true) (more accurately the numberb in location B is greater than or equal to the numbera in location A) THEN, the algorithm specifies B ← B − A (meaning the number b − a replaces the old b). Similarly, IF A > B, THEN A ← A − B. In mathematics and computer science, an algorithm ( i/ˈælɡərɪðəm/ AL-gə-ri-dhəm) is a step-by-step procedure for calculations. Informal definition[edit] While there is no generally accepted formal definition of "algorithm," an informal definition could be "a set of rules that precisely defines a sequence of operations Boolos & Jeffrey (1974, 1999) offer an informal meaning of the word in the following quotation: The term "enumerably infinite" means "countable using integers perhaps extending to infinity."
Mechanism From Wikipedia, the free encyclopedia Mechanism may refer to: