Expressiveness of Generic Process Shape Types

Shape types are a general concept of process types which work for many process calculi. We extend the previously published Poly* system of shape types to support name restriction. We evaluate the expressiveness of the extended system by showing that shape types are more expressive than an implicitly typed pi-calculus and an explicitly typed Mobile Ambients. We demonstrate that the extended system makes it easier to enjoy advantages of shape types which include polymorphism, principal typings, and a type inference implementation.Comment: Submitted to Trustworthy Global Computing (TGC) 2010

A pattern-based approach to a cell tracking ontology

Time-lapse microscopy has thoroughly transformed our understanding of biological motion and developmental dynamics from single cells to entire organisms. The increasing amount of cell tracking data demands the creation of tools to make extracted data searchable and interoperable between experiment and data types. In order to address that problem, the current paper reports on the progress in building the Cell Tracking Ontology (CTO): An ontology framework for describing, querying and integrating data from complementary experimental techniques in the domain of cell tracking experiments. CTO is based on a basic knowledge structure: the cellular genealogy serving as a backbone model to integrate specific biological ontologies into tracking data. As a first step we integrate the Phenotype and Trait Ontology (PATO) as one of the most relevant ontologies to annotate cell tracking experiments. The CTO requires both the integration of data on various levels of generality as well as the proper structuring of collected information. Therefore, in order to provide a sound foundation of the ontology, we have built on the rich body of work on top-level ontologies and established three generic ontology design patterns addressing three modeling challenges for properly representing cellular genealogies, i.e. representing entities existing in time, undergoing changes over time and their organization into more complex structures such as situations

An ontology framework for developing platform-independent knowledge-based engineering systems in the aerospace industry

This paper presents the development of a novel knowledge-based engineering (KBE) framework for implementing platform-independent knowledge-enabled product design systems within the aerospace industry. The aim of the KBE framework is to strengthen the structure, reuse and portability of knowledge consumed within KBE systems in view of supporting the cost-effective and long-term preservation of knowledge within such systems. The proposed KBE framework uses an ontology-based approach for semantic knowledge management and adopts a model-driven architecture style from the software engineering discipline. Its phases are mainly (1) Capture knowledge required for KBE system; (2) Ontology model construct of KBE system; (3) Platform-independent model (PIM) technology selection and implementation and (4) Integration of PIM KBE knowledge with computer-aided design system. A rigorous methodology is employed which is comprised of five qualitative phases namely, requirement analysis for the KBE framework, identifying software and ontological engineering elements, integration of both elements, proof of concept prototype demonstrator and finally experts validation. A case study investigating four primitive three-dimensional geometry shapes is used to quantify the applicability of the KBE framework in the aerospace industry. Additionally, experts within the aerospace and software engineering sector validated the strengths/benefits and limitations of the KBE framework. The major benefits of the developed approach are in the reduction of man-hours required for developing KBE systems within the aerospace industry and the maintainability and abstraction of the knowledge required for developing KBE systems. This approach strengthens knowledge reuse and eliminates platform-specific approaches to developing KBE systems ensuring the preservation of KBE knowledge for the long term

Bounded Refinement Types

We present a notion of bounded quantification for refinement types and show how it expands the expressiveness of refinement typing by using it to develop typed combinators for: (1) relational algebra and safe database access, (2) Floyd-Hoare logic within a state transformer monad equipped with combinators for branching and looping, and (3) using the above to implement a refined IO monad that tracks capabilities and resource usage. This leap in expressiveness comes via a translation to "ghost" functions, which lets us retain the automated and decidable SMT based checking and inference that makes refinement typing effective in practice.Comment: 14 pages, International Conference on Functional Programming, ICFP 201

Foundational Extensible Corecursion

This paper presents a formalized framework for defining corecursive functions safely in a total setting, based on corecursion up-to and relational parametricity. The end product is a general corecursor that allows corecursive (and even recursive) calls under well-behaved operations, including constructors. Corecursive functions that are well behaved can be registered as such, thereby increasing the corecursor's expressiveness. The metatheory is formalized in the Isabelle proof assistant and forms the core of a prototype tool. The corecursor is derived from first principles, without requiring new axioms or extensions of the logic

Heap Abstractions for Static Analysis

Heap data is potentially unbounded and seemingly arbitrary. As a consequence, unlike stack and static memory, heap memory cannot be abstracted directly in terms of a fixed set of source variable names appearing in the program being analysed. This makes it an interesting topic of study and there is an abundance of literature employing heap abstractions. Although most studies have addressed similar concerns, their formulations and formalisms often seem dissimilar and some times even unrelated. Thus, the insights gained in one description of heap abstraction may not directly carry over to some other description. This survey is a result of our quest for a unifying theme in the existing descriptions of heap abstractions. In particular, our interest lies in the abstractions and not in the algorithms that construct them. In our search of a unified theme, we view a heap abstraction as consisting of two features: a heap model to represent the heap memory and a summarization technique for bounding the heap representation. We classify the models as storeless, store based, and hybrid. We describe various summarization techniques based on k-limiting, allocation sites, patterns, variables, other generic instrumentation predicates, and higher-order logics. This approach allows us to compare the insights of a large number of seemingly dissimilar heap abstractions and also paves way for creating new abstractions by mix-and-match of models and summarization techniques.Comment: 49 pages, 20 figure

Modal logics are coalgebraic

Applications of modal logics are abundant in computer science, and a large number of structurally different modal logics have been successfully employed in a diverse spectrum of application contexts. Coalgebraic semantics, on the other hand, provides a uniform and encompassing view on the large variety of specific logics used in particular domains. The coalgebraic approach is generic and compositional: tools and techniques simultaneously apply to a large class of application areas and can moreover be combined in a modular way. In particular, this facilitates a pick-and-choose approach to domain specific formalisms, applicable across the entire scope of application areas, leading to generic software tools that are easier to design, to implement, and to maintain. This paper substantiates the authors' firm belief that the systematic exploitation of the coalgebraic nature of modal logic will not only have impact on the field of modal logic itself but also lead to significant progress in a number of areas within computer science, such as knowledge representation and concurrency/mobility

Widely Linear Kernels for Complex-Valued Kernel Activation Functions

Complex-valued neural networks (CVNNs) have been shown to be powerful nonlinear approximators when the input data can be properly modeled in the complex domain. One of the major challenges in scaling up CVNNs in practice is the design of complex activation functions. Recently, we proposed a novel framework for learning these activation functions neuron-wise in a data-dependent fashion, based on a cheap one-dimensional kernel expansion and the idea of kernel activation functions (KAFs). In this paper we argue that, despite its flexibility, this framework is still limited in the class of functions that can be modeled in the complex domain. We leverage the idea of widely linear complex kernels to extend the formulation, allowing for a richer expressiveness without an increase in the number of adaptable parameters. We test the resulting model on a set of complex-valued image classification benchmarks. Experimental results show that the resulting CVNNs can achieve higher accuracy while at the same time converging faster.Comment: Accepted at ICASSP 201

A Type Inference Algorithm for Secure Ambients

We consider a type discipline for the Ambient Calculus that associates ambients with security levels and constrains them to be traversed by or opened in ambients of higher security clearance only. We present a bottom-up algorithm that, given an untyped process $P$, computes a minimal set of constraints on security levels such that all actions during runs of $P$ are performed without violating the security level priorities. Such an algorithm appears to be a prerequisite to use type systems to ensure security properties in the web scenario

A Unified Approach for Representing Structurally-Complex Models in SBML Level 3

The aim of this document is to explore a unified approach to handling several of the proposed extensions to the SBML Level 3 Core specification. The approach is illustrated with reference to Simile, a modelling environment which appears to have most of the capabilities of the various SBML Level 3 package proposals which deal with model structure. Simile (http://www.simulistics.com) is a visual modelling environment for continuous systems modelling which includes the ability to handle complex disaggregation of model structure, by allowing the modeller to specify classes of object and the relationships between them.

The note is organised around the 6 packages listed on the SBML Level 3 Proposals web page (http://sbml.org/Community/Wiki/SBML_Level_3_Proposals) which deal with model structure, namely comp, arrays, spatial, geom, dyn and multi. For each one, I consider how the requirements which motivated the package can be handled using Simile's unified approach. Although Simile has a declarative model-representation language (in both Prolog and XML syntax), I use Simile diagrams and equation syntax throughout, since this is more compact and readable than large chunks of XML.

The conclusion is that Simile can indeed meet most of the requirements of these various packages, using a generic set of constructs - basically, the multiple-instance submodel, the concept of a relationship (association) between submodels, and array variables. This suggests the possibility of having a single SBML Level 3 extension package similar to the Simile data model, rather than a series of separate packages. Such an approach has a number of potential advantages and disadvantages compared with having the current set of discrete packages: these are discussed in this paper