Integrative priming occurs rapidly and uncontrollably during lexical processing

Lexical priming, whereby a prime word facilitates recognition of a related target word (e.g., nurse ? doctor), is typically attributed to association strength, semantic similarity, or compound familiarity. Here, the authors demonstrate a novel type of lexical priming that occurs among unassociated, dissimilar, and unfamiliar concepts (e.g., horse ? doctor). Specifically, integrative priming occurs when a prime word can be easily integrated with a target word to create a unitary representation. Across several manipulations of timing (stimulus onset asynchrony) and list context (relatedness proportion), lexical decisions for the target word were facilitated when it could be integrated with the prime word. Moreover, integrative priming was dissociated from both associative priming and semantic priming but was comparable in terms of both prevalence (across participants) and magnitude (within participants). This observation of integrative priming challenges present models of lexical priming, such as spreading activation, distributed representation, expectancy, episodic retrieval, and compound cue models. The authors suggest that integrative priming may be explained by a role activation model of relational integration

Using Semantic Technologies in Digital Libraries- A Roadmap to Quality Evaluation

Abstract. In digital libraries semantic techniques are often deployed to reduce the expensive manual overhead for indexing documents, maintaining metadata, or caching for future search. However, using such techniques may cause a decrease in a collection’s quality due to their statistical nature. Since data quality is a major concern in digital libraries, it is important to be able to measure the (loss of) quality of metadata automatically generated by semantic techniques. In this paper we present a user study based on a typical semantic technique use

Abstract Concepts: Sensory-Motor Grounding, Metaphors, and Beyond

Abstract In the last decade many researchers have obtained evidence for the idea that cognition shares processing mechanisms with perception and action. Most of the evidence supporting the grounded cognition framework focused on representations of concrete concepts, which leaves open the question how abstract concepts are grounded in sensory-motor processing. One promising idea is that people simulate concrete situations and introspective experiences to represent abstract concepts [Barsalou, L. W., & Wiemer-Hastings, K. (2005). Situating abstract concepts. In D. Pecher, & R. A. Zwaan (Eds.), Grounding cognition: The role of perception and action in memory, language, and thinking (pp. 129–163). Cambridge: Cambridge University Press.], although this has not yet been investigated a lot. A second idea, which more researchers have investigated, is that people use metaphorical mappings from concrete to abstract concepts [Lakoff, G., & Johnson, M. (1980). Metaphors we live by. Chicago: Chicago University Press.]. According to this conceptual metaphor theory, image schemas structure and provide sensory-motor grounding for abstract concepts. Although there is evidence that people automatically activate image schemas when they process abstract concepts, we argue that situations are also needed to fully represent meaning

Slang Analysis Based on Variant Information Extraction Focusing on the Time Series Topics

Recently, with the increase in the number of users of Social Networking Sites (SNS), online communications have become more and more common, raising the possibility of using big data on SNS to analyze the diversity of language. Japanese language uses a variety of character types that are combined to create words and phrases. Therefore, it is difficult to morphologically analyze such words and phrases, even though morphological analysis is a basic process in natural language processing. Words and phrases that are not registered in morphological analysis dictionaries are usually not defined strictly, and their semantic interpretation seems to vary depending on the individual. In this study, we chronologically analyze the topics related to slang on Twitter. In this paper, as a validation experiment, we conducted a topic analysis experiment chronologically by using the sequential Tweet data and discussing the difference of topic change according to the slang types

Automatic tolerance inspection through Reverse Engineering: a segmentation technique for plastic injection moulded parts

This work studies segmentations procedures to recognise features in a Reverse Engineering (RE) application that is oriented to computer-aided tolerance inspection of injection moulding die set-up, necessary to manufacture electromechanical components. It will discuss all steps of the procedures, from the initial acquisition to the final measure data management, but specific original developments will be focused on the RE post-processing method, that should solve the problem related to the automation of the surface recognition and then of the inspection process. As it will be explained in the first two Chapters, automation of the inspection process pertains, eminently, to feature recognition after the segmentation process. This work presents a voxel-based approach with the aim of reducing the computation efforts related to tessellation and curvature analysis, with or without filtering. In fact, a voxel structure approximates the shape through parallelepipeds that include small sub-set of points. In this sense, it represents a filter, since the number of voxels is less than the total number of points, but also a local approximation of the surface, if proper fitting models are applied. Through sensitivity analysis and industrial applications, limits and perspectives of the proposed algorithms are discussed and validated in terms of accuracy and save of time. Validation case-studies are taken from real applications made in ABB Sace S.p.A., that promoted this research. Plastic injection moulding of electromechanical components has a time-consuming die set-up. It is due to the necessity of providing dies with many cavities, which during the cooling phase may present different stamping conditions, thus defects that include lengths outside their dimensional tolerance, and geometrical errors. To increase the industrial efficiency, the automation of the inspection is not only due to the automatic recognition of features but also to a computer-aided inspection protocol (path planning and inspection data management). For this reason, also these steps will be faced, as the natural framework of the thesis research activity. The work structure concerns with six chapters. In Chapter 1, an introduction to the whole procedure is presented, focusing on reasons and utilities of the application of RE techniques in industrial engineering. Chapter 2 analyses acquisition issues and methods that are related to our application, describing: (a) selected hardware; (b) adopted strategy related to the cloud of point acquisition. In Chapter 3, the proposed RE post-processing is described together with a state of art about data segmentation and surface reconstruction. Chapter 4 discusses the proposed algorithms through sensitivity studies concerning thresholds and parameters utilised in segmentation phase and surface reconstruction. Chapter 5 explains briefly the inspection workflow, PDM requirements and solution, together with a preliminary assessing of measures and their reliability. These three chapters (3, 4 and 5) report final sections, called “Discussion”, in which specific considerations are given. Finally, Chapter 6 gives examples of the proposed segmentation technique in the framework of the industrial applications, through specific case studies

Remote sensing in forestry: Application to the Amazon region

The utilization of satellite remote sensing in forestry is reviewed with emphasis on studies performed for the Brazilian Amazon Region. Timber identification, deforestation, and pasture degradation after deforestation are discussed

Continuous Improvement Through Knowledge-Guided Analysis in Experience Feedback

Continuous improvement in industrial processes is increasingly a key element of competitiveness for industrial systems. The management of experience feedback in this framework is designed to build, analyze and facilitate the knowledge sharing among problem solving practitioners of an organization in order to improve processes and products achievement. During Problem Solving Processes, the intellectual investment of experts is often considerable and the opportunities for expert knowledge exploitation are numerous: decision making, problem solving under uncertainty, and expert configuration. In this paper, our contribution relates to the structuring of a cognitive experience feedback framework, which allows a flexible exploitation of expert knowledge during Problem Solving Processes and a reuse such collected experience. To that purpose, the proposed approach uses the general principles of root cause analysis for identifying the root causes of problems or events, the conceptual graphs formalism for the semantic conceptualization of the domain vocabulary and the Transferable Belief Model for the fusion of information from different sources. The underlying formal reasoning mechanisms (logic-based semantics) in conceptual graphs enable intelligent information retrieval for the effective exploitation of lessons learned from past projects. An example will illustrate the application of the proposed approach of experience feedback processes formalization in the transport industry sector