A Turing machine has an important role in education in the field of computer science, as it is a milestone in courses related to automata theory, theory of computation and computer architecture. Its value is also recognized in the Computing Curricula proposed by the Association for Computing Machinery (ACM) and IEEE Computer Society. In this paper we present a physical implementation of the Tur...

Computing Machine Models To gage the computational power of a family of mechanical computers, we will use a widely known abstract computational model known as the Turing machine, defined in this section. The Turing machine. The Turing machine model formulated by Alan Turing (1937) was the first complete mathematical model of an abstract computing machine that possessed universal computing power...

The Universal Function Theorem (UFT) originated in 1930s with the work of Alan Turing, who proved the existence of a universal Turing machine for computations on strings over a finite alphabet. This stimulated the development of stored-program computers. Classical computability theory, including the UFT and the theory of semicomputable sets, has been extended by Tucker and Zucker to abstract ma...

fuzzy rule-based classification system (frbcs) is a popular machine learning technique for classification purposes. one of the major issues when applying it on imbalanced data sets is its biased to the majority class, such that, it performs poorly in respect to the minority class. however many cases the minority classes are more important than the majority ones. in this paper, we have extended ...

Machine intelligence dates back to 1936, when Alan Turing proposed the idea of a universal mathematics machine, a theoretical concept in the mathematical theory of computability. Turing and Emil Post independently proved that determining the decidability of mathematical propositions is equivalent to asking what sort of sequences of a finite number of symbols can be recognized by an abstract mac...

The benchmark for computation is typically given as Turing computability; the ability for a computation to be performed by a Turing Machine. Many languages exploit (indirect) encodings of Turing Machines to demonstrate their ability to support arbitrary computation. However, these encodings are usually by simulating the entire Turing Machine within the language, or by encoding a language that d...

In this note I would like to confront some conventional concepts of information processing (selective dissipation) with the facts of molecular biophysics. There are a number of theoretical computers which provide formalizations of the intuitive notion of effective (or algorithmic) information processing. The best known of these is the Turing machine. This is a finite automaton along with a memo...

The year 2012 marks the 40th anniversary of the publication of the influential paper “Reducibility among combinatorial problems” by Richard Karp [37]. This paper was the first to demonstrate the wide applicability of the concept now known as NP-completeness, which had been introduced the previous year by Stephen Cook and Leonid Levin, independently. 2012 also marks the 100th anniversary of the ...

We investigate the complexity of query processing in the logical data model (LDM). We use two measures: data complexity, which is complexity with respect to the size of the data, and expression complexity, which is complexity with respect to the size of the expressions denoting the queries. Our investigation shows that while the operations of product and union are essentially rst-order operatio...

We outline a theory of evolutionary computation using a formal model of evolutionary computation--the Evolutionary Turing Machine--which is introduced as the extension of the Turing Machine model. Evolutionary Turing Machines provide a better and a more complete model for evolutionary computing than conventional Turing Machines, algorithms, and Markov chains. The convergence and convergence rat...