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Programming in several dimensions
 In Proc. SoftVis ’99, (Ed A Quigley
, 1999
"... Writing a program to solve a problem is a process that can be divided into two phases: first, we invent a mental model of the solution; secondly, we map the mental model onto a physical representation. The mental model is multidimensional and syntaxfree; in today’s textual programming languages, th ..."
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Cited by 2 (1 self)
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Writing a program to solve a problem is a process that can be divided into two phases: first, we invent a mental model of the solution; secondly, we map the mental model onto a physical representation. The mental model is multidimensional and syntaxfree; in today’s textual programming languages, the physical representation is singledimensional and syntaxburdened. In fact, it hasn’t changed greatly since Algol 60. Mapping from one representation to the other has remained a painstaking and errorprone task, in spite of the ready availability of immensely faster computers, massive amounts of memory, highresolution graphics displays, and powerful graphic input mechanisms. The Hyperprogramming paradigm exploits these capabilities. A hyperprogramming language employs different visualisations for different program components for example one visual syntax is suitable for visualising algorithms and another is suitable for visualising subroutine nesting. Each visualisation is designed for minimal overlap with the others, and where overlap is essential, hyperlinks between the views are automatically provided to allow easy navigation between them, and automatic updating of shared information. HyperPascal was developed as a vehicle for exploring this idea. In creating a program, a HyperPascal programmer edits information in three main visualisations: • the action window visualisation, which represents algorithms using a visual language based on structure diagrams; • the data structure templates visual component, which represents dynamic data structure algorithms using beforeandafter pictures • the scope window visualisation, which represents declarations as a nested visualisation analogous to conventional subroutine nesting
Defining Virtual Reality: Dimensions Determining Telepresence
 JOURNAL OF COMMUNICATION
, 1992
"... Virtual reality (VR) is typically defined in terms of technological hardware. This paper attempts to cast a new, variablebased definition of virtual reality that can be used to classify virtual reality in relation to other media. The defintion of virtual reality is based on concepts of "presen ..."
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Cited by 534 (0 self)
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;presence" and "telepresence," which refer to the sense of being in an environment, generated by natural or mediated means, respectively. Two technological dimensions that contribute to telepresence, vividness and interactivity, are discussed. A variety of media are classified according to these dimensions
Usability Analysis of Visual Programming Environments: a `cognitive dimensions' framework
 JOURNAL OF VISUAL LANGUAGES AND COMPUTING
, 1996
"... The cognitive dimensions framework is a broadbrush evaluation technique for interactive devices and for noninteractive notations. It sets out a small vocabulary of terms designed to capture the cognitivelyrelevant aspects of structure, and shows how they can be traded off against each other. T ..."
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Cited by 510 (13 self)
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The cognitive dimensions framework is a broadbrush evaluation technique for interactive devices and for noninteractive notations. It sets out a small vocabulary of terms designed to capture the cognitivelyrelevant aspects of structure, and shows how they can be traded off against each other
The MarkovKrein correspondence in several dimensions
, 1998
"... We compute the joint moments of several linear functionals with respect to a Dirichlet random measure and some of its generalizations. Given a probability distribution on a space X, let M = M denote the random probability measure on X known as Dirichlet random measure with the parameter distributi ..."
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Cited by 8 (0 self)
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We compute the joint moments of several linear functionals with respect to a Dirichlet random measure and some of its generalizations. Given a probability distribution on a space X, let M = M denote the random probability measure on X known as Dirichlet random measure with the parameter
Topology of Kleinian Groups in Several Dimensions
"... this paper I organize higherdimensional Kleinian groups according to the topology of their limit sets, trying to contrast and compare them with the Kleinian subgroups of PSL(2; C ). In this setting, one of the key questions that I was trying to address is the interaction between the geometry and to ..."
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theorem and its failure in higher dimensions (section 6). Next I consider the representation varieties of Kleinian groups and topological and geometrical constrains on Kleinian groups in higher dimensions. Lastly, I discuss generalizations of Kleinian groups: uniformly quasiconformal groups, fundamental
The MarkovKrein correspondence in several dimensions
, 2004
"... Given a probability distribution τ on a space X, letM = Mτ denote the random probability measure on X known as Dirichlet random measure with parameter distribution τ. We prove the formula ..."
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Given a probability distribution τ on a space X, letM = Mτ denote the random probability measure on X known as Dirichlet random measure with parameter distribution τ. We prove the formula
A tutorial on support vector machines for pattern recognition
 Data Mining and Knowledge Discovery
, 1998
"... The tutorial starts with an overview of the concepts of VC dimension and structural risk minimization. We then describe linear Support Vector Machines (SVMs) for separable and nonseparable data, working through a nontrivial example in detail. We describe a mechanical analogy, and discuss when SV ..."
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Cited by 3319 (12 self)
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The tutorial starts with an overview of the concepts of VC dimension and structural risk minimization. We then describe linear Support Vector Machines (SVMs) for separable and nonseparable data, working through a nontrivial example in detail. We describe a mechanical analogy, and discuss when
Homological Algebra of Mirror Symmetry
 in Proceedings of the International Congress of Mathematicians
, 1994
"... Mirror Symmetry was discovered several years ago in string theory as a duality between families of 3dimensional CalabiYau manifolds (more precisely, complex algebraic manifolds possessing holomorphic volume elements without zeroes). The name comes from the symmetry among Hodge numbers. For dual Ca ..."
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Cited by 529 (3 self)
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Mirror Symmetry was discovered several years ago in string theory as a duality between families of 3dimensional CalabiYau manifolds (more precisely, complex algebraic manifolds possessing holomorphic volume elements without zeroes). The name comes from the symmetry among Hodge numbers. For dual
A solution to Plato’s problem: The latent semantic analysis theory of acquisition, induction, and representation of knowledge
 PSYCHOLOGICAL REVIEW
, 1997
"... How do people know as much as they do with as little information as they get? The problem takes many forms; learning vocabulary from text is an especially dramatic and convenient case for research. A new general theory of acquired similarity and knowledge representation, latent semantic analysis (LS ..."
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Cited by 1772 (10 self)
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(LSA), is presented and used to successfully simulate such learning and several other psycholinguistic phenomena. By inducing global knowledge indirectly from local cooccurrence data in a large body of representative text, LSA acquired knowledge about the full vocabulary of English at a comparable
N Degrees of Separation: MultiDimensional Separation of Concerns
 IN PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING
, 1999
"... Done well, separation of concerns can provide many software engineering benefits, including reduced complexity, improved reusability, and simpler evolution. The choice of boundaries for separate concerns depends on both requirements on the system and on the kind(s) of decompositionand composition a ..."
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Cited by 514 (8 self)
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given formalism supports. The predominant methodologies and formalisms available, however, support only orthogonal separations of concerns, along single dimensions of composition and decomposition. These characteristics lead to a number of wellknown and difficult problems. This paper describes a new
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