Abstract : In this research paper, I will give you an abstract level of familiarization with Hyper Computation. In my work, I will give you an introduction about hyper computation and then relate the hyper computation with turing machine. Later in this research paper, we analyze different hyper machines and some resources which are very essential in developing a hyper computing machine, and then see some implications of hyper computation in the field of computer science. Introduction (Hyper Computation): The turing machine was developed for computation. Alan turing introduced the imaginary machine to the world, which could take input (these inputs usually represents the various mathematical objects), and then produces some output after
Moreover, he or she can carry out different "tests" with the aid of a computer. For instance, one can study strange attractors, chaotic dynamics, and fractal sets. By this we may talk about a specific experimentation in mathematics. The use of this kind of testing in mathematical research results in describing it as an experimental science. The goal of the paper is to attempt to answer the questions: does mathematics really transform into experimental or quasi-experimental science and does mathematics vary from axiomatic-deductive science into empirical science?
At this point there are two options depending on whether the model works: A) If it is a satisfactory mathematical model, then: Ability to make further predictions. OR B) If it is not a satisfactory mathematical model, then: Revision of model. To create a working mathematical model you would begin by working out what the problem or issue you are trying to predict or solve is. When doing this you would describe the system and work out any variables that might be needed. You must then simplify the model by making assumptions about what changes might affect the overall outcome.
1. Introduction Design variables are important to be conducted the appropriate experiment analyzing and getting the accurate values for integer, discrete, zero-one (binary), and continuous variables. The researchers should classify design factors before the experiment is conducted. In literature, there are several factors such as quantitative, qualitative, discrete, continuous, zero-one (binary), non-zero-one (non-binary), controlled and uncontrolled variables (Sanchez & Wan, 2009). Quantitative variables get numerical values.
«British museum algorithm», is quite enough for Logic (logical form). On the other hand, the process of «problem-solving» can be investigated in the light of the following question: «how is it possible to build a piece of correct reasoning?». This task is considered in Heuristic. Heuristic investigates general principles and methods of «problem-solving». Computer Heuristic (computer heuristic method) is a system of rules (a rule) for essential reducing the complete search, i.e.
Ma (1999) explains that the understanding of elementary mathematical ideas in essence underpin the development of all mathematics. Ma (1999) further suggests that these elementary mathematical concepts establish the basis on which future mathematical thinking is constructed. Mathematics can often be taught in discrete and separate ways to cover a specific curriculum. However Richhart (1994) and Nodding (1993) imply that teachers should not simply cover the curriculum but rather uncover it. Booker (2010) supports these suggestions by explaining that mathematics needs to be viewed as a cohesive body of knowledge rather than as a series of fragmented ideas.
The standard Data Analysis and Probability is based around formulating questions, selecting and using appropriate methods, and developing and evaluating predictions based on data, and understanding and applying basic concepts of probability. The standard Reasoning and Proof is described in NCTM as recognizing reasoning and proofs as fundamental aspects of mathematics, making and investigating conjectures, and developing arguments and proofs. The Reasoning and Proof standard also enables students to select and use various types of methods, much like Date Analysis and Probability. Probability is rooted from the word probe, meaning to discover what is not excessively effectively available or reasonable. The word proof stems from the same rooting, that gives details to comprehend what is assumed to be true.
With decimal search, you first draw the graph of the curve that is to be investigated, and look for where the curve passes through the x axis, as these points are where the roots are. But as you cannot guess exactly where the roots are, you take intervals: the two points surrounding where the curve passes through the x axis. These points are taken as whole numbers. The next step is then to investigate where exactly between this interval, the value of f(x) changes to positive, or negative. To do this you go one decimal point further between these values.
When needing to understand the true issue and coming to a valuable solution, time may be considered an enormous issue as implementation of a solution may require quick action. Quantitative research As indicated, research requires a process in order to collect data and analyze the data to come to a correct conclusion. Quantitative research is different from the qualitative research as researched above. Quantitative research focuses on amounts or quantities of one or multiple variables (Leedy, & Ormrod, 2010). To further explain, Fischler (2010) states, “a type of educational research in which the researcher decides what to study; asks specific, narrow questions; collects quantifiable data from participants; analyzes these numbers using statistics; and conducts the inquiry in an unbiased, objective manner” (p. 12).
These open ended questions may help the claim presented above. The first question has similar pretenses as the claim and may have similar responses. The second question involving whether we can prove that language is shaped by our vocabulary is also quite similar to the claim in that it is trying to prove that language is indeed shaped by our vocabulary and not the other way around. I agree that what we know is shaped by the vocabulary we are familiar with. In the area of math, Calculus is directly impacted by the words and vocabulary we do know.