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Some textbooks of formal languages and automata theory implicitly state the structural equality of the binary n-dimensional de Bruijn graph and the state diagram of minimum state deterministic finite automaton which accepts regular language (0+1)*1(0+1)^{n-1}. Although the isomorphism in binary case is relatively easy to prove, it is desirable to rigorously prove such an isomorphism in general k-ary case. To achieve this purpose, the author introduces a new computational model, called "colored finite automata (CFA)," and give a certain characterization of the general k-ary de Bruijn graphs by regular languages. The second purpose of this study is to investigate the potential of this automaton with multi-colored accepting states. By the way, when CFA is nondeterministic (NCFA), it is desirable that the colors of accepting states are unmixed (i.e., there are no inputs that are accepted with differently colored accepting states) in order to pursuit the accurate identification. Thus, the author proposes the three decision problems (Unmixedness Verification problem, Unmixedness Partitioning problem, and Unmixedness Extension problem) concerning unmixedness and show that UV, UP, and UE problems are shown to be NLOG-complete, P, and NP-complete, respectively. The author also illustrates the applications of colored finite automata, e.g. to existing regular expression engines and model checking tools for the purpose of improvement of their efficiency and conveniency. Next, the author introduces "colored pushdown automaton (CPDA)" which is an ordinary pushdown automaton with colored accepting states. It is shown that while the computational complexity of the above-mentioned UV, UP, and UE problems of CPDA are all undecidable, restriction of CPDA are all undecidable, restriction of CPDAs to unambiguous ones simplifies some problems of them to the permanently true problems. In this way, the concept of colored accepting states can be applied to a wide range of automata that have a set of accepting states and expected to be useful in a wide range of theoretical and practical field of automata applications in the future.

The purpose of this paper is to present a macroeconomic model, in which the bank determine the loan interest rate and the deposit interest rate by assuming the loan demand curve and the deposit supply curve. The bank adjusts the loan interest rate and the deposit interest rate while observing the difference between the assumed demand for loan and the actual demand for loan.

Taiwan has not yet been singed the “Convention on Nuclear Safety; CNS” that was adopted by the International Atomic Energy Agency （IAEA） in 1994. However, if these international activities help promote nuclear safety, Taiwan must participate in it and fulfill its related obligations. Therefore, despite Taiwan being a non-member state to the CNS, it is required by the Convention to act as a member state to meet all the requirements addressed in the CNS. Ensuring the public trust of nuclear safety regulations in the most important policy issue for the location, operation, waste disposal and off-commissioning of nuclear power plants, etc. As part of an international comparison of nuclear safety regulatory bodies in the East Asian region, this note organizes and evaluates the independence and transparency of Taiwan’s regulatory bodies.

The Japanese Bridge Management System (J-BMS) RC version consists of the following three subsystems: (1) a bridge maintenance database system (J-BMS DB), (2) a concrete bridge rating expert system (RC-BREX) and (3) a maintenance plan optimization system (MPOS). Especially, in this paper, the RC-BREX system for deteriorating concrete bridges is described based on how to construct from a hierarchical neural network in order to carry out fuzzy inference and machine learning by using the neural network with the back-propagation method. Furthermore, the comparisons between diagnostic results by bridge experts and those of the proposed system are presented so as to demonstrate the validity of the system’s learning capability by using the training set for machine learning which obtained from inspection on actual in-service bridges and questionnaire surveys by bridge experts.

We investigate symmetric equilibria of mutual reinforcement learning when both players alternately learn the optimal memory-two strategies against the oppo-nent in the repeated prisoners' dilemma game. We provide a necessary condi-tion for memory-two deterministic strategies to form symmetric equilibria. We then provide three examples of memory-two deterministic strategies which form symmetric mutual reinforcement learning equilibria. We also prove that mu-tual reinforcement learning equilibria formed by memory-two strategies are also mutual reinforcement learning equilibria when both players use reinforcement learning of memory-n strategies with n > 2.