Serguei A. Mokhov

Distributed Modular Audio Recognition Framework (DMARF) and its Applications Over Web Services

In this work we present the software architecture design and implementation of a Distributed Modular Audio Recognition Framework (DMARF), and its applications, such as Speaker Identification, that can run distributively over the Web Services architecture using XML-RPC. We describe some of the challenges occurred during the design and implementation, the advantages and disadvantages of such an implementation, and its possible future directions.

Design and Implementation of Context Calculus in the GIPSY Environment

GIPSY is a platform providing a framework for the compilation and execution of programs written in intensional programming languages of the Lucid family. While maintaining its use of intensionality, over the years, Lucid constantly underwent changes in its syntax, and its semantics is getting more and more generalized. Throughout this hectic evolution of the language, various systems for the evaluation of Lucid programs were developed. Due to lack of ability to adapt to the syntax and semantic changes of the language, all of them met with doom as new evolutions of the language were proposed. Set in this evolutionary aspect of Lucid, GIPSY aims at easing the development of the Lucid family of intensional programming languages by providing a common system into which variants of Lucid can be compiled and executed and, more interestingly, developed in the future. One of the latest evolutions of Lucid is the language Lucx, permitting the explicit use of contexts as first-class atomic entities. This paper presents the integration of Lucxs context calculus into GIPSY. We define the notion of context according to Lucx, its syntax and semantics, as well as operators on such contexts. We then present how context entities have been abstracted into implementation classes and embedded into GIPSY.

Towards Syntax and Semantics of Hierarchical Contexts in Multimedia Processing Applications Using MARFL

We focus on defining context expressions in terms of initial syntax and semantics for an intensional MARF language, MARFL. It is there to allow scripting Modular Audio Recognition Framework (MARF)-based applications as context-aware, where the notion of context represents coarse-grained and fine-grained configuration details of a given MARF instance and a set of overloaded context operators borrowed from the Generic Intensional Programming Language (GIPL) @ and # to help with the task. This is a preliminary research on MARFL that has considerable practical implications on the usability of MARFs resources and beyond. In this paper we focus exclusively on the context specification for multimedia pattern recognition tasks and available MARF resources for its applications.

Introducing MARF: a Modular Audio Recognition Framework and its Applications for Scientific and Software Engineering Research

MARF is an open-source research platform and a collection of voice/sound/speech/text and natural language processing (NLP) algorithms written in Java and arranged into a modular and extensible framework facilitating addition of new algorithms. MARF can run distributively over the network and may act as a library in applications or be used as a source for learning and extension. A few example applications are provided to show how to use the framework. There is an API reference in the Javadoc format as well as this set of accompanying notes with the detailed description of the architectural design, algorithms, and applications. MARF and its applications are released under a BSD-style license and is hosted at SourceForge.net. This document provides the details and the insight on the internals of MARF and some of the mentioned applications.

Towards Autonomic Specification of Distributed MARF with ASSL: Self-healing

In this paper, we discuss our work towards self-healing property specification of an autonomic behavior in the Distributed Modular Audio Recognition Framework (DMARF) by using the Autonomic System Specification Language (ASSL). ASSL aids in enhancing DMARF with an autonomic middleware that enables it to perform in autonomous systems that theoretically require less-to-none human intervention. Here, we add an autonomic middleware layer to DMARF by specifying the core four stages of the DMARF’s pattern-recognition pipeline as autonomic elements managed by a distinct autonomic manager. We devise the algorithms corresponding to this specification.

Advances in the Design and Implementation of a Multi-tier Architecture in the GIPSY Environment with Java

We present advances in the software engineering design and implementation of the multi-tier run-time system for the General Intensional Programming System (GIPSY) by further unifying the distributed technologies used to implement the Demand Migration Framework (DMF) in order to streamline distributed execution of hybrid intensional-imperative programs using Java.

Using the General Intensional Programming System (GIPSY) for Evaluation of Higher-Order Intensional Logic (HOIL) Expressions

The General Intensional Programming System (GIPSY) has been built around the Lucid family of intensional programming languages that rely on the higher-order intensional logic (HOIL) to provide context-oriented multidimensional reasoning of intensional expressions. HOIL combines functional programming with various intensional logics to allow explicit context expressions to be evaluated as first-class values that can be passed as parameters to functions and return as results with an appropriate set of operators defined on contexts. GIPSYs frameworks are implemented in Java as a collection of replaceable components for the compilers of various Lucid dialects and the demand-driven eductive evaluation engine that can run distributively. GIPSY provides support for hybrid programming models that couple intensional and imperative languages for a variety of needs. Explicit context expressions limit the scope of evaluation of math expressions (effectively a Lucid program is a mathematics or physics expression constrained by the context) in tensor physics, regular math in multiple dimensions, etc., and for cyberforensic reasoning as one of the use-cases of interest. Thus, GIPSY is a support testbed for HOIL-based languages some of which enable such reasoning, as in formal cyberforensic case analysis with event reconstruction. In this paper we discuss the GIPSY architecture, its evaluation engine and example use-cases.

A type system for hybrid intensional-imperative programming support in GIPSY

We describe a type system for a platform called the General Intensional Programming System (GIPSY), designed to support intensional programming languages built upon intensional logic and their imperative counter-parts for the intensional execution model. In GIPSY, the type system glues the static and dynamic typing between intensional and imperative languages in its compiler and runtime environments to support the intensional evaluation of expressions written in various dialects of the intensional programming language Lucid. The intensionality makes expressions to explicitly take into the account a multidimensional context of evaluation with the context being a first-class value that serves a number of applications that need the notion of context to proceed. We describe and discuss the properties of such a type system as well as particularities of the design and implementation of it.

Autonomic specification of self-protection for distributed MARF with ASSL

This paper presents practical results of our endeavor towards formal specification and code generation of the Autonomic Distributed Modular Audio Recognition Framework (AD-MARF) system. We used the Autonomic System Specification Language (ASSL) to design and specify a self-protecting mechanism that must be incorporated by DMARF. Our overall goal is to have an autonomic computing layer covering DMARF by specifying autonomic properties at each of the pattern recognition stages of the same. Here we present results that complement our related work on the self-healing and self-optimizatin autonomic properties.

Object-Oriented Intensional Programming: Intensional Java/Lucid Classes

This article introduces Object-Oriented Intensional Programming (OO-IP), a new hybrid language between Object-Oriented and Intensional Programming Languages in the sense of the latest evolutions of Lucid. This new hybrid language - called JOOIP for Java Object Oriented Intensional Programming - combines the essential characteristics of Lucid and Java, and introduces the notion of object streams which makes it is possible that each element in a Lucid stream to be an object with embedded intensional properties. Interestingly, this hybrid language also brings to Java objects the power to explicitly express and manipulate the notion of context, creating the novel concept of intensional object, i.e. objects whose evaluation is context-dependent, which are demonstrated to be translatable into standard objects.