Computational Interpretation Research Articles

Uniqueness logic

A uniqueness type system is used to distinguish values which are referenced at most once from values which may be referenced an arbitrary number of times in a program. Uniqueness type systems are used in the Clean and Mercury programming languages to provide efficiently updatable data-structures and I/O without compromising referential transparency. In this paper we establish a Curry–Howard–Lambek equivalence between a form of uniqueness types and a ‘resource-sensitive’ logic. This logic is similar to intuitionistic linear logic, however the ∘ modality, which moderates the structural rules in the antecedent in the same way as ! , is introduced via the dual ? rules. We discuss the categorical proof theory and models of this new logic, as well as its computational interpretation.

Recent advances in array comparative genomic hybridization technologies and their applications in human genetics

Array comparative genomic hybridization (array CGH) is a method used to detect segmental DNA copy number alterations. Recently, advances in this technology have enabled high-resolution examination for identifying genetic alterations and copy number variations on a genome-wide scale. This review describes the current genomic array platforms and CGH methodologies, highlights their applications for studying cancer genetics, constitutional disease and human variation, and discusses visualization and analytical software programs for computational interpretation of array CGH data.

A computational view of implicit coercions in type theory

Type isomorphisms are pairs of functions are mutually inverse. In principle, type isomorphisms, viewed as back-and-forth coercions, could be used in the context of proof assistants based on dependent type theory in order to relate equivalent representations of mathematical notions, for example, the polar and cartesian representations of complex numbers. However, the coercions that map one representation into another are not mutually inverse because of the intensional nature of dependent type theories. Consequently, the standard concept of type isomorphisms has limited applicability in the context of proof assistants.In order to circumvent this problem, we develop a computational interpretation of implicit coercions that allows for the definition of back-and-forth coercions without requiring them to be mutually inverse. We illustrate the usefulness of our approach in a number of formal developments that require us to navigate between different representations of mathematical objects or structures. We also discuss important meta-theoretical properties of our interpretation.

Nonparametric and Semi-parametric Estimation of Efficient Frontier

This paper has presented a nonparametric approach to estimate the deterministic frontier model with unknown function form. Single index modeling and partially linear modeling techniques have been modified for estimation of a semi-parametric deterministic frontier model. Those approaches are free from functional form specification and error term distribution assumption. The methods are very attractive for computational simplicity and straightforward interpretation. They can be extended to estimate the stochastic frontier model with more parametric assumption. At the center is the kernel estimation of the continuous density and conditional expectation. These kernel estimations are used as the instruments in estimating expectation of efficiency level, production frontier, and firm's specific inefficiency.

Variography for Model Selection in Local Polynomial Regression with Spatial Data

In this work, we apply variographic techniques from spatial statistics to the problem of model selection in local polynomial regression with multivariate data. These techniques permit selection of the kernel and smoothing matrix with less computational load and interpretation of the regularity of the regression function in different directions. Moreover, they may represent the only feasible alternative for problems of a certain dimensionality.

Interpretation of Shotgun Proteomic Data

The shotgun proteomic strategy based on digesting proteins into peptides and sequencing them using tandem mass spectrometry and automated database searching has become the method of choice for identifying proteins in most large scale studies. However, the peptide-centric nature of shotgun proteomics complicates the analysis and biological interpretation of the data especially in the case of higher eukaryote organisms. The same peptide sequence can be present in multiple different proteins or protein isoforms. Such shared peptides therefore can lead to ambiguities in determining the identities of sample proteins. In this article we illustrate the difficulties of interpreting shotgun proteomic data and discuss the need for common nomenclature and transparent informatic approaches. We also discuss related issues such as the state of protein sequence databases and their role in shotgun proteomic analysis, interpretation of relative peptide quantification data in the presence of multiple protein isoforms, the integration of proteomic and transcriptional data, and the development of a computational infrastructure for the integration of multiple diverse datasets.

On the Expressiveness of Higher Dimensional Automata: (Extended Abstract)

In this paper I compare the expressive power of several models of concurrency based on their ability to represent causal dependence. To this end, I translate these models, in behaviour preserving ways, into the model of higher dimensional automata, which is the most expressive model under investigation. In particular, I propose four different translations of Petri nets, corresponding to the four different computational interpretations of nets found in the literature.I also extend various equivalence relations for concurrent systems to higher dimensional automata. These include the history preserving bisimulation, which is the coarsest equivalence that fully respects branching time, causality and their interplay, as well as the ST-bisimulation, a branching time respecting equivalence that takes causality into account to the extent that it is expressible by actions overlapping in time. Through their embeddings in higher dimensional automata, it is now well-defined whether members of different models of concurrency are equivalent.

A computational interpretation of Dolev–Yao adversaries

The Dolev–Yao model is a simple and useful framework in which to analyze security protocols, but it assumes that the adversary is extremely limited. We show that it is possible for the results of this model to remain valid even if the adversary is given additional power. In particular, we show that there exist situations in which Dolev–Yao adversary can be viewed as a valid abstraction of all realistic adversaries. We do this in a number of steps: (1) The Dolev–Yao model places strong assumptions on the adversary. We capture those assumptions in the computational model (an alternate framework with a very powerful adversary) as a non-malleability property of public-key encryption. (2) We prove an Abadi–Rogaway-style indistinguishability property (J. Cryptol. 15(2) (2002) 103–127) for the public-key setting. That is, we show that if two Dolev–Yao expressions are indistinguishable to the Dolev–Yao adversary, then their computational interpretations (via a chosen-ciphertext secure encryption scheme) are computationally indistinguishable. (3) We show that any encryption scheme that satisfies the indistinguishability property also satisfies our (more natural) non-malleability property.

Map Theory: From Well-Foundation to Antifoundation

Map Theory is a powerful extension of type-free lamba-calculus (with only a few term constants added). Due to Klaus Grue, it was designed to be a common foundation for Computer Sciences and for Mathematics. All the primitive notions of first-order logic and set theory, including truth values, connectives and quantifiers, set-membership and set-equality, are interpreted as terms. All the usual set-theoretic constructs, including inductive data-types, get computational interpretations. Now, Grue’s version of Map Theory is founded, in the sense that it only considers mathematical sets or classes which are well-founded with respect to the membership relation. In [19], we have shown that it was possible to design an alternative version which takes non-well-founded sets into account, and allows for co-inductive reasoning over them. This new version opens the way to a direct representation of co-inductive data-types and of circular processes and phenomena in Map Theory. In this article, we give parallel presentations of the two versions of Map Theory and of their relations with ZFC. We also give a flavor of the proofs of their relative consistency with respect to the existence of a strongly inaccessible cardinal. These proofs take place inside the κ-continuous semantics, which is an extension of Scott’s continuous semantics (where κ = ω) to any regular cardinal κ.

Computational Interpretation of Vibrational Optical Activity: The ROA Spectra of (4S)‐4‐Methylisochromane and the (4S)‐Isomers of Galaxolide®

AbstractThe reliable computation of Raman‐optical‐activity (ROA) spectra of molecules of the size of the title compounds has, until now, not been possible. We show that our rarefied basis sets yield results in good agreement with the experimental data for (4S)‐4‐methylisochromane (=(4S)‐3,4‐dihydro‐4‐methyl‐1H‐2‐benzopyran; 1), provided the equilibrium between the pseudo‐equatorial and the pseudo‐axial conformers is taken into account. Comparison between the measured and the computed ROA back‐scattering spectra allows the unequivocal assignment of the absolute configuration of the molecule. Comparison with more‐approximate calculations for the larger (4S)‐isomers of Galaxolide® (2), which contain the (4S)‐4‐methylisochromane moiety, shows large‐scale group frequencies on the same chiral fragments of the two molecules. The data confirm that ROA can be generated by interactions extending over several bonds, i.e., over larger distances than can be probed by NMR spectroscopy. Thus, the absolute configuration at C(7) of Galaxolide® is assignable independently of that at C(4). The computation of ROA for forward‐scattering, which will soon be measurable for Galaxolide®, suggests that this scattering geometry provides additional stereochemical information that will be valuable in situations where absolute configurations at several stereogenic centers have to be assigned.

Nuclear morphometry of neoplastic cells as a method for diagnosis of histiocytoma, mastocytoma and transmissible venereal tumor in dogs

Image analysis has been used in medicine and veterinary science as an increasingly important auxiliary tool for histopathology evaluation, because of its potential for decreasing the intrinsic subjectivity of the human visual analysis. However, the geometrical features currently used are often inefficient, not always leading to correct diagnosis. The present work has as its main objective to suggest several approaches to geometric and texture characterization of the cell nuclei, characterized by low computational cost, rapid analysis and sound biological interpretation and good agreement with the visual analysis by expert pathologists. We consider digital images of histological slides obtained from histiocytoma, mastocytoma and transmissible venereal tumors in dogs. Segmented cell nuclei of these tumors were evaluated morphometrically considering the features normally used in medicine together with novel features suggested in the present work, applied in order to characterize the distribution and morphology of the nucleoli and heterochromatin inside the nuclei. Statistical characterization of the obtained results was performed through variance and discriminant analysis, leading to the identification of the most important features. The approach proposed in this article has been verified to be an effective auxiliary tool for differential diagnosis of histiocytoma, mastocytoma and TVT in dogs. Its low computational cost allows fast morphometric evaluation, paving the way for real-time tumor diagnosis.

Dynamic gain control of dopamine delivery in freely moving animals.

Activity changes in a large subset of midbrain dopamine neurons fulfill numerous assumptions of learning theory by encoding a prediction error between actual and predicted reward. This computational interpretation of dopaminergic spike activity invites the important question of how changes in spike rate are translated into changes in dopamine delivery at target neural structures. Using electrochemical detection of rapid dopamine release in the striatum of freely moving rats, we established that a single dynamic model can capture all the measured fluctuations in dopamine delivery. This model revealed three independent short-term adaptive processes acting to control dopamine release. These short-term components generalized well across animals and stimulation patterns and were preserved under anesthesia. The model has implications for the dynamic filtering interposed between changes in spike production and forebrain dopamine release.

Online retrieval, processing, and visualization of primate connectivity data from the CoCoMac database.

Connectivity is the key to understanding distributed and cooperative brain functions. Detailed and comprehensive data on large-scale connectivity between primate brain areas have been collated systematically from published reports of experimental tracing studies. Although the majority of the data have been made easily available for online retrieval, the multiplicity of brain maps and the precise requirements of anatomical naming limit the intuitive access to the data. The quality of data retrieval can be improved by observing a small set of conventions in data representation. Standardized interfaces open up further opportunities for automated search and retrieval, for flexible visualization of data, and for interoperability with other databases. This article provides a discussion and examples in text and image of the capabilities of the online interface to the CoCoMac database of primate connectivity. These serve to point out sources of potential confusion and failure, and to demonstrate the automated interfacing with other neuroinformatics resources that facilitate selection and processing of connectivity data, for example, for computational modelling and interpretation of functional imaging studies.

A conceptual framework for interpretation of airborne geophysical data

The new generation of high quality airborne geophysical data is rich in information reflecting the complexity and variability of the subsurface, yet methodological approaches to extracting this geological information have remained largely unchanged and poorly documented. The vast majority of literature either discusses computational interpretation techniques or reports the results of a geological interpretation of geophysical data. In this paper we address this problem by presenting a conceptual interpretation framework to represent the general transformation of geophysical data into geological knowledge. The framework is based on five fundamental tasks ? spatial pattern identification, spatial correlation, computational interpretation, geological inference and target identification. Our purpose in developing this framework is to enable the development of robust, repeatable computer-assisted interpretation methodologies. For a specific interpretation problem, the framework can be used to design an appropriate interpretation methodology that clearly identifies which tasks are assigned to which data set(s), and how these tasks are linked to produce the required outcomes of the interpretation. In particular, it enables the interpreter to consider using computer-based analysis to complete some aspects of the interpretation that might normally be completed using a conventional, manual approach. For example, in this paper we apply the framework to develop an interpretation methodology for a multivariate geophysical study of dryland salinity. This structured approach does not sacrifice the vital human-centred elements of the interpretation, but rather enables the interpreter to explore avenues to integrate those human-centred tasks with computer-assisted processes.

A functional approach for temporal $\times$ modal logics

This work is focused on temporal × modal logics. We study the representation of properties of functions of interest because of their possi- ble computational interpretations. The semantics is exposed in an algebraic style, and the definability of the basic properties of the functions is anal- ysed. We introduce minimal systems for linear time with total functions as well as with a class of partial functions (those with uniform domain). More- over, completeness proofs are offered for these minimal systems. Finally, functional-validity is compared with T × W -validity and Kamp-validity.

Directional relative position between objects in image processing: a comparison between fuzzy approaches

The importance of describing relationships between objects has been highlighted in works in very different areas, including image understanding. Among these relationships, directional relative position relations are important since they provide an important information about the spatial arrangement of objects in the scene. Such concepts are rather ambiguous, they defy precise definitions, but human beings have a rather intuitive and common way of understanding and interpreting them. Therefore in this context, fuzzy methods are appropriate to provide consistent definitions that integrate both quantitative and qualitative knowledge, thus providing a computational representation and interpretation of imprecise spatial relations, expressed in a linguistic way, and including quantitative knowledge. Several fuzzy approaches have been developed in the literature, and the aim of this paper is to review and compare them according to their properties and according to the types of questions they seek to answer.

Characterization of protein structure and function at genome scale with a computational prediction pipeline.

Recent advances in high-throughput production capabilities for biological data such as genomic sequence (1,2), large-scale gene expression data (3-5), genomescale protein-protein interactions (6,7), and protein structures (8), arc revolutionizing the biological sciences. Essential to this new revolution are capabilities to computationally interpret large quantities of biological data generated under various experimental conditions and build mathematical models that fit these data. The combination of on-line bioinformatics tools and easy access to the high-speed Internet has made it generally possible to facilitate such computational steps and make biological discoveriesin silicoin a highly efficient manner. By utilizing various bioinformatics prediction, analysis and modeling tools, one can quickly generate hypotheses and theoretical models, which could then guide the design of experiments for further validation. The paradigm that links and integrates systematic data generation, computational data interpretation, and experimental validation is clearly providing a new and powerful way for conducting biological research. The focus of this paper is on (a) development of new computational tools for interpretation of large quantity of genomic sequence data for structural and functional inference and (b) example applications of these tools to studies of microbial genomes, particularlycyanobacterialgenomes.KeywordsStructure PredictionProtein Structure PredictionQuery ProteinFunctional AssignmentComputational PipelineThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Fatigue Fracture Investigation of Cemented Carbide Tools in Gear Hobbing, Part 1: FEM Modeling of Fly Hobbing and Computational Interpretation of Experimental Results

Gear hobbing is a highly utilized flexible manufacturing process for massive production of external gears. However, the complex geometry of cutting hobs is responsible for the almost exclusive utilization of high-speed steel (HSS) as cutting tool material. The limited cutting performance of HSS, even coated HSS, restricts the application of high cutting speeds and restricts the full exploitation of modern CNC hobbing machine tools. The application of cemented carbide tools was considered as a potential alternative to modern production requirements. In former investigations an experimental variation of gear hobbing, the so-called fly hobbing was applied, in order to specify the cutting performance of cemented carbide tools in gear production. These thorough experiments indicated that cracks, which were not expected, might occur in specific cutting cases, leading to the early failure of the entire cutting tool. In order to interpret computationally the reasons for these failures, an FEM simulation of the cutting process was developed, supported by advanced software tools able to determine the chip formation and the cutting forces during gear hobbing. The computational results explain sufficiently the failure mechanisms and they are quite in line with the experimental findings. The first part of this paper applies the verified parametric FEM model for various cutting cases, indicating the most risky cutting teeth with respect to their fatigue danger. In a step forward, the second part of the paper illustrates the effect of various technological and geometric parameters to the expected tool life. Therefore, the optimization of the cutting process is enabled, through the proper selection of cutting parameters, which can eliminate the failure danger of cemented carbide cutting tools, thus achieving satisfactory cost effectiveness.

A judgmental reconstruction of modal logic

We reconsider the foundations of modal logic, following Martin-Löf's methodology of distinguishing judgments from propositions. We give constructive meaning explanations for necessity and possibility, which yields a simple and uniform system of natural deduction for intuitionistic modal logic that does not exhibit anomalies found in other proposals. We also give a new presentation of lax logic and find that the lax modality is already expressible using possibility and necessity. Through a computational interpretation of proofs in modal logic we further obtain a new formulation of Moggi's monadic metalanguage.

Decidability of Linear Affine Logic

The propositional linear logic is known to be undecidable. In the current paper we prove that the full propositional linear affine logic containing all the multiplicatives, additives, exponentials, and constants is decidable. The proof is based on a reduction of linear affine logic to sequents of specific “normal forms” and on a generalization of Kanovich computational interpretation of linear logic adapted to these normal forms.