Abstract Discusses differences between a code and a cipher. Requirements of each; how each works. History of encryption. Enigma machine of World War II. Pre-computer encrption. Development of computer program to encrypt data. Function of a "hash" (a number generated from text & smaller than the text itself). Privacy issues. Future of algorithms.
From the Paper "Encryption and Hash Algorithms
Introduction
Stephen Levy (2001), reporting on the latest "unbreakable code" begins his report by quoting Edgar Allan Poe. "It may roundly be asserted that human ingenuity cannot concoct a cipher which human ingenuity cannot resolve" (Levy, 2001, 45). This article was selected to lead off this discussion of encryption because of two elements of confusion.
First, the headline read "An Unbreakable Code?" and the article was about enciphering and deciphering, also called "encryption" and ?decryption.? This is a common, and often-repeated mistake, one which can confuse the very field of study. A "code" is not a "cipher" anymore than a "tennis ball" is a ?cabbage.?
Abstract This paper discusses statistical analysis as a dynamic form of study that evolves over time to meet developing needs and to exploit developing capabilities and technologies. The author points out that statistical analysis is the process through which data becomes knowledge and is a science to assist one in making decisions under conditions of uncertainty. The paper relates that the most appropriate logic bases for the discipline of statistical analysis in the contemporary period are rational, quantitative, positivist and causality.
Table of Contents
Introduction: Reflections on Statistics
Reviewing Statistical Analysis
Defining Statistical Analysis
Alternative Logic Bases for Statistical Analysis
Rational Model versus Naturalistic Model.
Quantitative Model versus Qualitative Model.
Positivist Model versus Normative Model.
Causality Model versus Plausibility Model
Exploratory Model versus Confirmatory Model.
Randomization Model.
Conclusion: Reviewing Statistical Analysis.
Examining the Classical Model of Statistical Analysis
Descriptive Statistical Analysis
Exploratory Statistical Analysis
Inferential Statistical Analysis
Probability Theory and Classical Statistical Analysis
Conclusion: Classical Statistical Analysis
From the Paper "Descriptive statistical analysis describes the performance or activity of one group or class, without attempting to generalize about other groups or classes. Classification, description, and measurement are activities applicable to variables associated with social research. The classification of variables is based on an assumption that social units are comparable within the context of specific definitional criteria. A social researcher attempts to control variation through the classification of variables. The description of variables is an effort to assign some degree of uniqueness to each variable, in order to provide a basis for the establishment of relationships among variables. The measurement of the extent of the uniqueness of variables generates the quantitative indicators of the strength of the relationships between variables. The process of classification, description, and measurement facilitates the development of causal explanations for both regularities and variations in empirical phenomena. Comparisons are made according to the degree of differentiation of structure in data in relation to a common and less differentiated point of origin. Such comparability is dependent upon both the classification of the social unit and the dimension of that social unit that is being measured. The dimension is the variable being measured."
Abstract Resonance is a term belonging to the mathematics of sound, and to different fields of physics and applied physics. In music, resonance involves the cause of sound produced by musical instruments, in effects that affect standing waves of sound due to resonating strings and air columns that create different frequencies.
Abstract This paper is on David Hilbert and mathematics. He became famous for developing his "axiomatic" and "existential" methods. His proposal in 1900 of twenty-three problems for the coming century set the course of much subsequent mathematics. It was in this context that Hilbert came to be seen as the person who set the foundation for many mathematical questions.
Abstract This essay discusses Alfred North Whitehead's view of math and science in philosophy. His basic theme is that concrete entities are not enduring substances but events that are connected to each other by their space-time relations and qualitative and mathematical patterns. In Whitehead's view, time is differentiated from space by the acts of inheriting patterns from the past.
Abstract This paper is written on conceptual and procedural knowledge in mathematics. Procedural knowledge-or more appropriately skills-refers to the ability to physically solve a problem through the manipulation of mathematical skills: with pencil and paper, calculator, computer, etc. There is thus, in a theoretical sense, a difference between conceptual and procedural knowledge in mathematics.
Abstract This paper examines the prevailing attitude towards women in mathematics and explains why in our enlightened age, when women are as educated as men, they are still considered by many to be unequal to men in many fields.
Abstract This paper expounds the "Theory of Everything," starting with the pioneering theories of Newton's "Laws of Motion" and Einstein's "General Theory of Relativity," developing right through to the cutting-edge "string theory" research currently being conducted around the world today. It shows the importance of fields of study as seemingly diverse as calculus, differential geometry, electromagnetism, particle physics and quantum mechanics to the development of a "Theory of Everything". It also demonstrates how those with access to this theory can use the knowledge as power for anything, such as understanding stock markets using the premise that the stock market moving up over time means that these are not random movements and therefore should be explainable.
From the Paper "Stock markets exist over time and space (the geographical markets) that we are able to quantify and understand to a degree. Therefore, as with Einstein, we are fairly comfortable with the stock market in its familiar four dimensions. We have become accustomed to inflation; the rising of prices of goods rise over time and this is obviously a major reason for at least part of the upward rise of share prices. However, what happens when we explore the smaller dimensions " like the six unknown dimensions string theorists grapple with" Like the string theorists who know that subatomic matter exists but can't explain or predict its behavior, we often know what influences the stock market but are usually unable to predict it."
Abstract This paper examines how, for many who lack a strong grounding in math and science, the two are often associated as being the same. The purpose of this paper is to define mathematics and science, showing them as two distinct fields of inquiry and then to show how advances in theoretical mathematics contribute the framework needed for scientists in the study of quantum mechanics, a branch of physics, which in turn, is one of the many branches of science.
Outline
Introduction
Mathematics
Science
Quantum Mechanics
Mathematics and Quantum Mechanics
Science and Quantum Mechanics
From the Paper "Finally, applied mathematics is a term loosely applied to a range of studies which have significant use in the sciences, specifically the empirical sciences, (branches of science open to practical or experiential experimenting). Applied mathematics makes use of numerical methods and computer science, seeking concrete solutions to explicit mathematical problems. In science and technology it has a major use as a way to model and/or simulate natural phenomenon or events. Examples include using mathematical models in computer generated wind tunnel tests to predict the behavior of a given shape of a prototype airplane wing without resorting to expensive actual wind tunnel testing."
Abstract This paper explains how, in schools, statistical education is primarily taught in mathematics, yet statistical ideas are used in other subjects, including science and economics. It discusses why teachers and researchers need to constantly work towards improving statistical education, leading to a great deal of research in the field. This paper examines existing research to determine how statistical education research can be improved in the future.
From the Paper "Statistical education has become an important part of curriculums in all levels of education. At both the undergraduate and graduate levels, statistical literacy is now a key objective in many classrooms. As a result, statistics is now being taught across various disciplines and is rapidly becoming a prerequisite course for graduation, regardless of a student's major. The teaching and learning of statistics has recently increased dramatically in many schools. As a result, many U.S. states now emphasize and include statistical thinking in their statewide curriculum guidelines."