We present the excavation results from a Middle Neolithic site associated with the Funnel Beaker Culture. Within two overlying house phases, a recessed area was recorded, which had been constructed using different sized pebbles. The arrangement and form of the feature clearly indicated anthropogenic origin and is understood as belonging to one of the house phases. Consequently, it is interpreted as a cellar. Several pits and post holes are additional features that were recorded at the site and indicate the presence of a fence structure with up to seven parallel courses. In this paper, we present radiocarbon dates from the features and an age model for the construction and use of the cellar as well as the fences. Moreover, the site Nygårdsvej 3 will be placed in its regional archaeological landscape.

Substance-free phonology (SFP) is based on the hypothesis that phonological computation makes no reference to phonetic substance, and that phonological features are treated as arbitrary symbols for the purposes of computation. However, phonologists within the SFP tradition disagree about whether the content of phonological features is innate or learned (“emergent”), and if learned, whether the acquisition process is based on phonological patterning alone or refers to phonetic substance. In the present article we identify predictive differences between these accounts. We conclude that there is an innate basis to phonological features, but that featural content is not innate. We suggest that a hybrid phonetic-phonological approach to feature content acquisition may ultimately be the most successful.

We argue that the representational primes of the human phonological faculty, the so-called distinctive features, are innate and substance-free. Our arguments for the innateness of features are built on traditional and novel logical arguments, experimental evidence accumulating over recent decades, and somewhat detailed proposals about their neurobiological reality. As symbols in the brain, features are substance-free, that is, they are devoid of articulatory and acoustic content, or even any direct reference to such phenomena. This is consistent with our substance-free conception of phonological computation, an approach that eschews functionalist notions like markedness, ease of articulation, and so on. We also outline a neural model of the phonetics-phonology interface called Cognitive Phonetics, which transduces innate features to speech articulation and from speech acoustics. These extra-grammatical transduction procedures are also part of the human biological endowment, which leaves no room for language-specific phonetics in our theory of the externalization of language. We show how Cognitive Phonetics can account for traditionally recognized intersegmental coarticulation, as well as the previously unexplored intrasegmental coarticulation, strongly suggesting that the basic units of speech production are transduced features.

This article argues that phonological features have no substantive properties, instead, segments are assigned features by learning strategies set to the task of devising a computational system for a phonology that is consistent with the requirements of UG. I address two problems for such a substance-free model. The first is the Card-Grammar problem, which has been suggested to argue for universal substantive features, on the premise that, otherwise, language data cannot be stored in a fashion necessary to correct learning errors. The Card Grammar problem disappears, in a suitably modular theory of mind with learned interfaces, where the mind still can retain information not parsed in a particular grammar. The second problem is the need for a demonstration, not just an assertion, that a reasonable theory of grammar and learning which has no access to phonetic substance can yield a coherent system of feature assignments. This is accomplished by modeling the learning of features necessary for the phonology of Kerewe.

In French ditransitive sentences, certain person combinations of the two internal arguments cannot be expressed with two co-occurring clitics (a phenomenon referred to as the Person Case Constraint or PCC). To fill the interpretational gap created by this restriction, there is an alternative construction characterized as a “repair”, where the goal is realized as an independent phrase. The fact that the double-clitic construction and the repair construction are in complementary distribution led to a proposal of an interface algorithm that provides a way to repair a non-convergent structure. This article proposes an alternative account of the PCC, and claims that the complementarity between the PCC and its repair is instead accidental and is an artefact of the feature structure of arguments. The proposed account explains the unavailability of certain clitic combinations and some repairs independently, without resorting to a trans-derivational device like the previously proposed algorithm.

The importance of the Global Positioning System (GPS) and related electronic systems continues to increase in a range of environmental, engineering and navigation applications. However, civilian GPS signals are vulnerable to Radio Frequency (RF) interference. Spoofing is an intentional intervention that aims to force a GPS receiver to acquire and track invalid navigation data. Analysis of spoofing and authentic signal patterns represents the differences as phase, energy and imaginary components of the signal. In this paper, early-late phase, delta, and signal level as the three main features are extracted from the correlation output of the tracking loop. Using these features, spoofing detection can be performed by exploiting conventional machine learning algorithms such as K-Nearest Neighbourhood (KNN) and naive Bayesian classifier. A Neural Network (NN) as a learning machine is a modern computational method for collecting the required knowledge and predicting the output values in complicated systems. This paper presents a new approach for GPS spoofing detection based on multi-layer NN whose inputs are indices of features. Simulation results on a software GPS receiver showed adequate detection accuracy was obtained from NN with a short detection time.

This paper investigates the properties of plural agreement that is triggered by collective nouns in British English. Both singular and plural agreement are able to appear with these collective nouns, which are shown to be morphologically singular but semantically plural. Plural agreement, however, is systematically more restricted than singular agreement, appearing in a subset of the environments where singular agreement is allowed. Restrictions on plural come from the nature of agreement; semantic agreement features can only enter into agreement when the controller of agreement c-commands the target of agreement, whereas morphologically motivated agreement is not subject to the same structural restriction. This asymmetry between the two types of agreement is shown to arise from the proposal that Agree (Chomsky 2000, 2001) is distributed over the syntactic and post-syntactic components (Arregi & Nevins 2012).

The way the cognitive system scans the visual environment for relevant information – visual search in short – has been a long-standing central topic in vision science. From its inception as a research topic, and despite a number of promising alternative perspectives, the study of visual search has been governed by the assumption that a search proceeds on the basis of individual items (whether processed in parallel or not). This has led to the additional assumptions that shallow search slopes (at most a few tens of milliseconds per item for target-present trials) are most informative about the underlying process, and that eye movements are an epiphenomenon that can be safely ignored. We argue that the evidence now overwhelmingly favours an approach that takes fixations, not individual items, as its central unit. Within fixations, items are processed in parallel, and the functional field of view determines how many fixations are needed. In this type of theoretical framework, there is a direct connection between target discrimination difficulty, fixations, and reaction time (RT) measures. It therefore promises a more fundamental understanding of visual search by offering a unified account of both eye movement and manual response behaviour across the entire range of observed search efficiency, and provides new directions for research. A high-level conceptual simulation with just one free and four fixed parameters shows the viability of this approach.

The property generation task (i.e. “feature listing”) is often assumed to measure concepts. Typically, researchers assume implicitly that the underlying representation of a concept consists of amodal propositions, and that verbal responses during property generation reveal their conceptual content. The experiments reported here suggest instead that verbal responses during property generation reflect two alternative sources of information: the linguistic form system and the situated simulation system. In two experiments, properties bearing a linguistic relation to the word for a concept were produced earlier than properties not bearing a linguistic relation, suggesting the early properties tend to originate in a word association process. Conversely, properties produced later tended to describe objects and situations, suggesting that late properties tend to originate from describing situated simulations. A companion neuroimaging experiment reported elsewhere confirms that early properties originate in language areas, whereas later properties originate in situated simulation areas. Together, these results, along with other results in the literature, indicate that property generation is a relatively complex process, drawing on at least two systems somewhat asynchronously.

The inductive category formation framework, an influential set of theories of learning in psychology and artificial intelligence, is deeply flawed. In this framework a set of necessary and sufficient features is taken to define a category. Such definitions are not functionally justified, are not used by people, and are not inducible by a learning system. Inductive theories depend on having access to all and only relevant features, which is not only impossible but begs a key question in learning. The crucial roles of other cognitive processes (such as explanation and credit assignment) are ignored or oversimplified. Learning necessarily involves pragmatic considerations that can only be handled by complex cognitive processes.

We provide an alternative framework for learning according to which category definitions must be based on category function. The learning system invokes other cognitive processes to accomplish difficult tasks, makes inferences, analyses and decides among potential features, and specifies how and when categories are to be generated and modified. We also examine the methodological underpinnings of the two approaches and compare their motivations.

A method for solving the recognition of partially occluded parts is presented. It is based on the automatic generation of features from a set of primitive features which are configurations of pairs of fixed length segments of boundary edges of the parts. The procedure that creates the recognition features assigns a number in the range (0,1) that indicates the importance of the feature in the recognition strategy. This number is referred to as the feature's saliency. The method assumes that the parts that can occur in a scene come from a known set of parts. An example illustrates how automatically generated features can be used to count the number of identical parts in a heap.

The ability to understand the implications of the geometry of solid objects is an important aspect of intelligent behavior. This paper presents work designed to enable reasoning with relatively loose conceptualizations of geometry. The method operates by comparing target geometry to known geometry, and involves the manipulation of models based upon prototypes. In particular, three techniques of simplification, approximation, and transformation are discussed. Finally, an application of the method to the domain of stress concentration prediction is presented.

An approach to providing computational support for concurrent design is discussed in the context of an industrial cable harness design problem. Key issues include the development of an architecture that supports collaboration among specialists, the development of hierarchical representations that capture different characteristics of the design, and the decomposition of tasks to achieve a trade-off between efficiency and robustness. An architecture is presented in which the main design tasks are supported by agents – asynchronous and semiautonomous modules that automate routine design tasks and provide specialized interfaces for working on particular aspects of the design. The agent communication and coordination mechanisms permit members of an engineering team to work concurrently, at different levels of detail and on different versions of the design. The design is represented hierarchically, with detailed models maintained by the participating agents. Abstractions of the detailed models, called “agent model images,” are shared with other agents. In conjunction with the architecture and design representations, issues pertaining to the exchange of information among different views of the design, management of dependencies and constraints, and propagation of design changes are discussed.

The involvement of the left temporal lobe in semantics and object naming has been repeatedly demonstrated in the context of language comprehension; however, its role in the mechanisms and time course for the retrieval of an integrated object memory from its constituent features have not been well delineated. In this study, 19 young adults were presented with two features of an object (e.g., “desert” and “humps”) and asked to determine whether these two features were congruent to form a retrieval of a specific object (“camel”) or incongruent and formed no retrieval while event-related potentials (ERP) were recorded. Beginning around 750 ms the ERP retrieval and nonretrieval waveforms over the left anterior fronto-temporal region show significance differences, indicating distinct processes for retrievals and nonretrievals. In addition to providing further data implicating the left frontal-anterior temporal region in object memory/retrieval, the results provide insight into the time course of semantic processing related to object memory retrieval in this region. The likely semantic process at 750 ms in this task would be coactivation of feature representations common to the same object. The consistency of this finding suggests that the process is stable across individuals. The potential clinical applications are discussed. (JINS, 2008, 14, 815–822.)

Shepard has argued that a universal law should govern generalization across different domains of perception and cognition, as well as across organisms from different species or even different planets. Starting with some basic assumptions about natural kinds, he derived an exponential decay function as the form of the universal generalization gradient, which accords strikingly well with a wide range of empirical data. However, his original formulation applied only to the ideal case of generalization from a single encountered stimulus to a single novel stimulus, and for stimuli that can be represented as points in a continuous metric psychological space. Here we recast Shepard's theory in a more general Bayesian framework and show how this naturally extends his approach to the more realistic situation of generalizing from multiple consequential stimuli with arbitrary representational structure. Our framework also subsumes a version of Tversky's set-theoretic model of similarity, which is conventionally thought of as the primary alternative to Shepard's continuous metric space model of similarity and generalization. This unification allows us not only to draw deep parallels between the set-theoretic and spatial approaches, but also to significantly advance the explanatory power of set-theoretic models.

This paper describes a generic approach to guiding designers when making decisions during the early stages of design. The objective of the research is to enable designers to foresee unintended life-cycle consequences during mechanical component design. Engineering design is a process of evolving solutions to a design problem through the commitment of decisions. As a designer commits a new design decision, a more concrete design solution is generated. Decisions made can have intended and unintended consequences on the performance of the life phase activities that follow, such as manufacturing, assembly, and disposal. Many existing tools only consider the impact of the design solution on later life-cycle phases when the solution is almost complete. This makes changes expensive and difficult. This paper presents a novel approach to how consequences encountered in down stream life-cycle phases can be brought to the designer's attention early in generation of component form. For this purpose, a knowledge model has been derived from a phenomena model. The phenomena model describes how life-cycle consequences are generated during component synthesis. An insight into the representation of the resultant knowledge model is discussed through examples. The implementation of a prototype Knowledge Intensive CAD tool, entitled FORESEE, aimed at supporting life-oriented, feature-based component synthesis and exploration, is also described. The results of the evaluation of FORESEE with a range of designers show that by using the system designers are motivated to explore alternative design solutions and are able to make more informed design decisions. This highlights that the knowledge structure provides a base for extending feature-based component design to a ‘Design Synthesis for Multi-X’ approach.