Splicing system in Automata Theory: A review

The study of formal language theory rapidly evolves after Tom Head introduce his research on formal language theory in 1987. Splicing system involves the process of cutting and pasting on DNA molecules with the presence of restriction enzymes and ligase, respectively. A mathematical model of the splicing system has been developed by using the concept of formal language theory, which is a branch of theoretical computer science and applied discrete mathematics, and informational macromolecules. Over the year, theoretical results in splicing systems have contributed to new research in formal language theory focused on modelling of biochemical processes. In this paper, the relation between formal language theory and some related molecular biological terms are explored. In addition, new ideas in the framework of biomolecular science, for example, the design of automated enzymatic processes are then discussed. Then, a mutual relation that exist in these field is then explained. The regular language can be implemented in the splicing system to show the DFA structure in the splicing system

RULES BASED MODELING OF DISCRETE EVENT SYSTEMS WITH FAULTS AND THEIR DIAGNOSIS

Failure diagnosis in large and complex systems is a critical task. In the realm of discrete event systems, Sampath et al. proposed a language based failure diagnosis approach. They introduced the diagnosability for discrete event systems and gave a method for testing the diagnosability by first constructing a diagnoser for the system. The complexity of this method of testing diagnosability is exponential in the number of states of the system and doubly exponential in the number of failure types. In this thesis, we give an algorithm for testing diagnosability that does not construct a diagnoser for the system, and its complexity is of 4th order in the number of states of the system and linear in the number of the failure types. In this dissertation we also study diagnosis of discrete event systems (DESs) modeled in the rule-based modeling formalism introduced in [12] to model failure-prone systems. The results have been represented in [43]. An attractive feature of rule-based model is it\u27s compactness (size is polynomial in number of signals). A motivation for the work presented is to develop failure diagnosis techniques that are able to exploit this compactness. In this regard, we develop symbolic techniques for testing diagnosability and computing a diagnoser. Diagnosability test is shown to be an instance of 1st order temporal logic model-checking. An on-line algorithm for diagnosersynthesis is obtained by using predicates and predicate transformers. We demonstrate our approach by applying it to modeling and diagnosis of a part of the assembly-line. When the system is found to be not diagnosable, we use sensor refinement and sensor augmentation to make the system diagnosable. In this dissertation, a controller is also extracted from the maximally permissive supervisor for the purpose of implementing the control by selecting, when possible, only one controllable event from among the ones allowed by the supervisor for the assembly line in automaton models