Search results for "Computation"
showing 10 items of 7362 documents
Multimode entanglement in reconfigurable graph states using optical frequency combs
2017
Multimode entanglement is an essential resource for quantum information processing and quantum metrology. However, multimode entangled states are generally constructed by targeting a specific graph configuration. This yields to a fixed experimental setup that therefore exhibits reduced versatility and scalability. Here we demonstrate an optical on-demand, reconfigurable multimode entangled state, using an intrinsically multimode quantum resource and a homodyne detection apparatus. Without altering either the initial squeezing source or experimental architecture, we realize the construction of thirteen cluster states of various sizes and connectivities as well as the implementation of a secr…
Distributed Computing on Distributed Memory
2018
Distributed computation is formalized in several description languages for computation, as e.g. Unified Modeling Language (UML), Specification and Description Language (SDL), and Concurrent Abstract State Machines (CASM). All these languages focus on the distribution of computation, which is somewhat the same as concurrent computation. In addition, there is also the aspect of distribution of state, which is often neglected. Distribution of state is most commonly represented by communication between active agents. This paper argues that it is desirable to abstract from the communication and to consider abstract distributed state. This includes semantic handling of conflict resolution, e.g. i…
Semiautomatic Behavioral Change-Point Detection: A Case Study Analyzing Children Interactions With a Social Agent
2021
The study of human behaviors in cognitive sciences provides clues to understand and describe people’s personal and interpersonal functioning. In particular, the temporal analysis of behavioral dynamics can be a powerful tool to reveal events, correlations and causalities but also to discover abnormal behaviors. However, the annotation of these dynamics can be expensive in terms of temporal and human resources. To tackle this challenge, this paper proposes a methodology to semi-automatically annotate behavioral data. Behavioral dynamics can be expressed as sequences of simple dynamical processes: transitions between such processes are generally known as change-points. This paper describes th…
Grammars++ for modelling information in text
1999
Abstract Grammars provide a convenient means to describe the set of valid instances in a text database. Flexibility in choosing a grammar can be exploited to provide information modelling capability by designing productions in the grammar to represent entities and relationships of interest to database applications. Additional constraints can be specified by attaching predicates to selected nonterminals in the grammar. When used for database definition, grammars can provide the functionality that users have come to expect of database schemas. Extended grammars can also be used to specify database manipulation, including query, update, view definition, and index specification.
Predicting perceived visual complexity of abstract patterns using computational measures: The influence of mirror symmetry on complexity perception
2017
Visual complexity is relevant for many areas ranging from improving usability of technical displays or websites up to understanding aesthetic experiences. Therefore, many attempts have been made to relate objective properties of images to perceived complexity in artworks and other images. It has been argued that visual complexity is a multidimensional construct mainly consisting of two dimensions: A quantitative dimension that increases complexity through number of elements, and a structural dimension representing order negatively related to complexity. The objective of this work is to study human perception of visual complexity utilizing two large independent sets of abstract patterns. A w…
Editorial: Mining Scientific Papers: NLP-enhanced Bibliometrics
2019
International audience
Assessing 4th Grade Students’ Computational Thinking through Scratch Programming Projects
2020
Computational thinking (CT) has been introduced in primary schools worldwide. However, rich classroom-based evidence and research on how to assess and support students’ CT through programming are particularly scarce. This empirical study investigates 4th grade students’ (N = 57) CT in a comparatively comprehensive and fine-grained manner by assessing their Scratch projects (N = 325) with a framework that was revised from previous studies to aim towards enhancing CT. The results demonstrate in detail the various coding patterns and code constructs the students programmed in assorted projects throughout a programming course and the extent to which they had conceptual encounters with CT. Notab…
Intent Detection System Based on Word Embeddings
2018
Intent detection is one of the main tasks of a dialogue system. In this paper we present our intent detection system that is based on FastText word embeddings and neural network classifier. We find a significant improvement in the FastText sentence vectorization. The results show that our intent detection system provides state-of-the-art results on three English datasets outperforming many popular services.
Applications and Limitations of Robust Bayesian Bounds and Type II MLE
1994
Three applications of robust Bayesian analysis and three examples of its limitations are given. The applications that are reviewed are the development of an automatic Ockham’s Razor, outlier detection, and analysis of weighted distributions. Limitations of robust Bayesian bounds are highlighted through examples that include analysis of a paranormal experiment and a hierarchical model. This last example shows a disturbing difference between actual hierarchical Bayesian analysis and robust Bayesian bounds, a difference which also arises if, instead, a Type II MLE or empirical Bayes analysis is performed.
Word sense disamibiguation combining conceptual distance, frequency and gloss
2004
Word sense disambiguation (WSD) is the process of assigning a meaning to a word based on the context in which it occurs. The absence of sense tagged training data is a real problem for the word sense disambiguation task. We present a method for the resolution of lexical ambiguity which relies on the use of the wide-coverage noun taxonomy of WordNet and the notion of conceptual distance among concepts, captured by a conceptual density formula developed for this purpose. The formula we propose, is a generalised form of the Agirre-Rigau conceptual density measure in which many (parameterised) refinements were introduced and an exhaustive evaluation of all meaningful combinations was performed.…