What can the history of AI learn from the history of science?

There have been few attempts, so far, to document the history of artificial intelligence. It is argued that the historical sociology of scientific knowledge can provide a broad historiographical approach for the history of AI, particularly as it has proved fruitful within the history of science in recent years. The article shows how the sociology of knowledge can inform and enrich four types of project within the history of AI; organizational history; AI viewed as technology; AI viewed as cognitive science and historical biography. In the latter area the historical treatments of Darwin and Turing are compared to warn against the pitfalls of rational reconstructions of the past.     

Exporting water wave optimization concepts to modified simulated annealing algorithm for size optimization of truss structures with natural frequency constraints

This paper proposes an improved version of a recently proposed modified simulated annealing algorithm (MSAA) named as an improved MSAA (I-MSAA) to tackle the size optimization of truss structures with frequency constraint. This kind of problem is problematic because its feasible region is non-convex while the boundaries are highly non-linear. The main motivation is to improve the exploitative behavior of MSAA, taking concept from water wave optimization metaheuristic (WWO). An interesting concept of WWO is its breaking operation. Thirty functions extracted from the CEC2014 test suite and four benchmark truss optimization problems with frequency constraints are explored for the validity of the proposed algorithm. Numerical results indicate that I-MSAA is more reliable, stable and efficient than those found by other existing metaheuristics in the literature.

     

Code generation for a family of executable modelling notations

We are investigating semantically configurable model-driven engineering (MDE). The goal of this work is a modelling environment that supports flexible, configurable modelling notations, in which specifiers can configure the semantics of notations to suit their needs and yet still have access to the types of analysis tools and code generators normally associated with MDE. In this paper, we describe semantically configurable code generation for a family of behavioural modelling notations. The family includes variants of statecharts, process algebras, Petri Nets, and SDL88. The semantics of this family is defined using template semantics, which is a parameterized structured operational semantics in which parameters represent semantic variation points. A specific notation is derived by instantiating the family’s template semantics with parameter values that specify semantic choices. We have developed a code-generator generator (CGG) that creates a suitable Java code generator for a subset of derivable modelling notations. Our prototype CGG supports 26 semantics parameters, 89 parameter values, and 7 composition operators. As a result, we are able to produce code generators for a sizable family of modelling notations, though at present the performance of our generated code is about an order of magnitude slower than that produced by commercial-grade generators.     

A Taxonomy of Representation Strategies in Iconic Communication

Predicting whether the intended audience will be able to recognize the meaning of an icon or pictograph is not an easy task. Many icon recognition studies have been conducted in the past. However, their findings cannot be generalized to other icons that were not included in the study, which, we argue, is their main limitation. In this paper, we propose a comprehensive taxonomy of icons that is intended to enable the generalization of the findings of recognition studies. To accomplish this, we analyzed a sample of more than eight hundred icons according to three axes: lexical category, semantic category, and representation strategy. Three basic representation strategies were identified: visual similarity; semantic association; and arbitrary convention. These representation strategies are in agreement with the strategies identified in previous taxonomies. However, a greater number of subcategories of these strategies were identified. Our results also indicate that the lexical and semantic attributes of a concept influence the choice of representation strategy.     

Visual reasoning about social networks using centrality sensitivity

In this paper, we study the sensitivity of centrality metrics as a key metric of social networks to support visual reasoning. As centrality represents the prestige or importance of a node in a network, its sensitivity represents the importance of the relationship between this and all other nodes in the network. We have derived an analytical solution that extracts the sensitivity as the derivative of centrality with respect to degree for two centrality metrics based on feedback and random walks. We show that these sensitivities are good indicators of the distribution of centrality in the network, and how changes are expected to be propagated if we introduce changes to the network. These metrics also help us simplify a complex network in a way that retains the main structural properties and that results in trustworthy, readable diagrams. Sensitivity is also a key concept for uncertainty analysis of social networks, and we show how our approach may help analysts gain insight on the robustness of key network metrics. Through a number of examples, we illustrate the need for measuring sensitivity, and the impact it has on the visualization of and interaction with social and other scale-free networks.     

Model-based testing of software and systems: recent advances and challenges

Model-based testing is focused on testing techniques which rely on the use of models. The diversity of systems and software to be tested implies the need for research on a variety of models and methods for test automation. We briefly review this research area and introduce several papers selected from the 22nd International Conference on Testing Software and Systems (ICTSS).     

Word sense disambiguation for spam filtering

Spam has become a major issue in computer security because it is a channel for threats such as computer viruses, worms, and phishing. More than 86% of received e-mails are spam. Historical approaches to combating these messages, including simple techniques such as sender blacklisting or the use of e-mail signatures, are no longer completely reliable. Many current solutions feature machine-learning algorithms trained using statistical representations of the terms that most commonly appear in such e-mails. However, these methods are merely syntactic and are unable to account for the underlying semantics of terms within messages. In this paper, we explore the use of semantics in spam filtering by introducing a pre-processing step of Word Sense Disambiguation (WSD). Based upon this disambiguated representation, we apply several well-known machine-learning models and show that the proposed method can detect the internal semantics of spam messages.     

MSW devices for EW receiver applications

Conclusion Significant improvements are required in the performance of MSW dispersive delay lines and filter banks before they are ready for systems application. Typically delay lines with bandwidths of 1 GHz or greater, differential delays in the range 200 ns to 1s, and minimum phase errors (<±1 °) are required for large (40 dB) dynamic range compressive receivers. However, techniques are evolving (see rest of this issue) in this relatively new area of technology which will allow systems performance requirements on phase errors to be met. Possible approaches to low phase error dispersive delay lines include reflective arrays, stepped ground planes, and multiple YIG films. The stepped ground plane technique is the most advanced and uses an optimization approach to the delay-line design, which results in a minimum phase error [20]. Ultimately the minimum achievable phase error will be limited by reflections from transducers and multiple mode effects in the delay lines. The MSW compressive receiver requires parallel advances in high-speed digital processing techniques to achieve its full potential.The MSW filter bank provides a simple channelization technique applicable up to approximately 20 GHz. Narrowband channels with 10 dB insertion loss, 3 dB bandwidths of 10 to 40 MHz, and 50 dB bandwidths of 30 to 120 MHz are possible with the already demonstrated techniques. Broader bandwidth channels in the range 50 to 200 MHz with flat passband response require improved transducer design techniques. The channelized receiver does not require extremely high-speed operations but, since a large number of channels are involved, size and cost become very significant.     

Note on the use of the term subject in pre-1886 discussions of thought-transference experiments.

In response to K. Danzinger's (see record 1986-00068-001) suggestion that the first use of the term subject in the English-language psychological literature occurred in 1886 in the context of experiments involving the hypnotic state, the present author points out that there are examples of the use of the term in discussions of experiments on thought transference published by the Society for Psychical Research in the 1880's. (8 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Electrospun fibers based on porcine plasma: a rheological and morphological study

Iranian Polymer Journal - The present work focuses on the assessment of the ability of porcine plasma protein (PPP) to be electrospun satisfactorily to form fibre mats, and their rheological and...