ADS Formal Semantics

Abstract Database System (ADS) is a data model developed for an enduring medical information system where frequent changes in the conceptual schema are anticipated and multi-level abstraction is required. The mechanism of abstraction in ADS is based on the abstraction operator of the lamba calculus. The formal semantics of a subset of the ADS model is presented using the denotational specification method

RNA-Protein Structure Classifiers Incorporated into Second-Generation Statistical Potentials

Computational modeling of RNA-protein interactions remains an important endeavor. However, exclusively all-atom approaches that model RNA-protein interactions via molecular dynamics are often problematic in their application. One possible alternative is the implementation of hierarchical approaches, first efficiently exploring configurational space with a coarse-grained representation of the RNA and protein. Subsequently, the lowest energy set of such coarse-grained models can be used as scaffolds for all-atom placements, a standard method in modeling protein 3D-structure. However, the coarse-grained modeling likely will require improved ribonucleotide-amino acid potentials as applied to coarse-grained structures. As a first step we downloaded 1,345 PDB files and clustered them with PISCES to obtain a non-redundant complex data set. The contacts were divided into nine types with DSSR according to the 3D structure of RNA and then 9 sets of potentials were calculated. The potentials were applied to score fifty thousand poses generated by FTDock for twenty-one standard RNA-protein complexes. The results compare favorably to existing RNA-protein potentials. Future research will optimize and test such combined potentials

A quick search method for audio signals based on a piecewise linear representation of feature trajectories

This paper presents a new method for a quick similarity-based search through long unlabeled audio streams to detect and locate audio clips provided by users. The method involves feature-dimension reduction based on a piecewise linear representation of a sequential feature trajectory extracted from a long audio stream. Two techniques enable us to obtain a piecewise linear representation: the dynamic segmentation of feature trajectories and the segment-based Karhunen-L\'{o}eve (KL) transform. The proposed search method guarantees the same search results as the search method without the proposed feature-dimension reduction method in principle. Experiment results indicate significant improvements in search speed. For example the proposed method reduced the total search time to approximately 1/12 that of previous methods and detected queries in approximately 0.3 seconds from a 200-hour audio database.Comment: 20 pages, to appear in IEEE Transactions on Audio, Speech and Language Processin

Back Propagation with Integer Arithmetic

The present work investigates the significance of arithmetic precision in neural network simulation. Noting that a biological brain consists of a large number of cells of low precision, we try to answer the question: With a fixed size of memory and CPU cycles available for simulation, does a larger sized net with less precision perform better than smaller sized one with higher precision? We evaluate the merits and demerits of using low precision integer arithmetic in simulating backpropagation networks. Two identical backpropagation simulators, ibp and fbp, were constructed on Mac II, ibp with 16 bits integer representations of network parameters such as activation values, back-errors, and weights; and fbp with 96 bits floating point representations of the same parameters. The performance of the two stimulators are compared in solving the same Boolean mapping problem, the sine transfer function with eight binary inputs and one analog output. The speed-up ratio from fbp to ibp is a single training cycle in approximately 7.3 for smaller networks and 4.2 for larger ones. However, for total time necessary to obtain a solution net, the speed-up ratio is 163 for the smaller nets, and 121 for the larger nets, because ibp requires much less number of training cycles than fbp. We also found that networks trained by integer arithmetic have more generalization capabilities than those trained by floating point arithmetic. At present time we have no explanation on this matter

Gauss-Jordan Elimination By VLSI Mech-Connected Processors

It is shown that a mesh-connected n x (n+m) toroidal array of processors can perform Gauss-Jordan elimination without pivoting, on an n x (n+m) matrix, in 4n+m-1 steps, each step involving at most two artithmetic operations for every processor

Relational Completeness of Show and Tell Visual Programming Language

In this paper we present the database applications of the Show and Tell Language (STL) and demonstrate the relational completeness of the language. STL is a visual programming language designed for novice computer users who are not familiar with keyboarding. A program can be constructed by using only a pointing device, except for textual data entry. A program can be constructed by using only a pointing device, except for textual data entry. Various programming concepts such as subroutine, iteration, recursion, concurrency, exception, and so forth are represented by two-dimensional graphic patterns and icons. The language is used to test the feasibility of keyboardless programming, Currently the language is implemented on the Apple Macintosh personal computer. In this paper we will present, first, the Show and Tell language primitives, then simple database applications through examples, and finally the representation of the five basic operations in relational algebra; difference, union, Cartesian product, projection, and selection; all using the Show and Tell visual constructs. This demonstrates that STL is a visual relational data query language which is complete in the sense of Codd

Determinacy of Hierarchical Dataflow Model

A parallel computation model suitable for icon based visual programming languages is proposed. The model is uses to design a functional programming language for school children. A computation is specified by boxes and arrows forming a partially ordered set of nested boxes. Loops and Boolean data tokens are eliminated from the traditional dataflow model. Block structures are logical consistency (exception) are added. A declarative semantics of the model is defined formally. Using the formalism it is proved that the model is determinate