A new framework has been developed to express variant and invariant properties of functions operating on a binary vector space. This framework allows for manipulation of dynamic logic using basic operations and permutations. Novel representations of binary functional spaces are presented. Current ideas of binary functional spaces are extended and additional conditions are added to describe new function representation schemes: F code and C code.Sizes of the proposed functional space representation schemes were determined. It was found that the complete representation for any set of functions operating on a binary sequence of numbers is larger than previously thought. The complete representation can only be described using a structure having a space of size 2 2 n  2 n ! for any given space of functions acting on a binary sequence of length n. The framework, along with the proposed coding schemes provides a foundational theory of variant and invariant logic in software and electricelectronic technology and engineering, and has uses in the analysis of the stability of rule-based, dynamic binary systems such as cellular automata.

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In this paper we propose a new dynamic model for knowledge in knowledge management. To analyze problems and relevant restrictions, two well-accepted knowledge representation models are discussed. The new model, Executable Knowledge Model (EKM), can distinguish foreground and background knowledge and it defines a determinable boundary for executable and nonexecutable knowledge in knowledge management. This model provides strong executable and testable properties of knowledge in knowledge management to guide further knowledge management development. J. P. T. Mo et al. (eds.), Global Engineering, Manufacturing and Enterprise Networks

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Stream cipher, DNA cryptography and DNA analysis are the most important R&D fields in both Cryptography and Bioinformatics. HC-256 is an emerged scheme as the new generation of stream ciphers for advanced network security. From a random sequencing viewpoint, both sequences of HC-256 and real DNA data may have intrinsic pseudo-random properties respectively. In a recent decade, many DNA sequencing projects are developed on cells, plants and animals over the world into huge DNA databases. Researchers notice that mammalian genomes encode thousands of large noncoding RNAs (lncRNAs), interact with chromatin regulatory complexes, and are thought to play a role in localizing these complexes to target loci across the genome. It is a challenge target using higher dimensional visualization tools to organize various complex interactive properties as visual maps. The Variant Map System (VMS) as an emerging scheme is systematically proposed in this paper to apply multiple maps that used four Meta symbols as same as DNA or RNA representations. System architecture of key components and core mechanism on the VMS are described. Key modules, equations and their I/O parameters are discussed. Applying the VM System, two sets of real DNA sequences from both sample human (noncoding DNA) and corn (coding DNA) genomes are collected in comparison with pseudo DNA sequences generated by HC-256 to show their intrinsic properties in higher levels of similar relationships among relevant DNA sequences on 2D maps. Sample 2D maps are listed and their characteristics are illustrated under controllable environment. Visual results are briefly analyzed to explore their intrinsic properties on selected genome sequences.