Deposits of clastic carbonate-dominated (calciclastic) sedimentary slope systems in the rock record have been identified mostly as linearly-consistent carbonate apron deposits, even though most ancient clastic carbonate slope deposits fit the submarine fan systems better. Calciclastic submarine fans are consequently rarely described and are poorly understood. Subsequently, very little is known especially in mud-dominated calciclastic submarine fan systems. Presented in this study are a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) that reveals a >250 m thick calciturbidite complex deposited in a calciclastic submarine fan setting. Seven facies are recognised from core and thin section characterisation and are grouped into three carbonate turbidite sequences. They include: 1) Calciturbidites, comprising mostly of highto low-density, wavy-laminated bioclast-rich facies; 2) low-density densite mudstones which are characterised by planar laminated and unlaminated muddominated facies; and 3) Calcidebrites which are muddy or hyper-concentrated debrisflow deposits occurring as poorly-sorted, chaotic, mud-supported floatstones. These

Phd by thesis

Real and Complex Analysis

Newness and distinctiveness is claimed in the features of ornamentation as shown inside the broken line circle in the accompanying representation.

Display screen or portion thereof with graphical user interface

An intelligent automated assistant system engages with the user in an integrated, conversational manner using natural language dialog, and invokes external services when appropriate to obtain information or perform various actions. The system can be implemented using any of a number of different platforms, such as the web, email, smartphone, and the like, or any combination thereof. In one embodiment, the system is based on sets of interrelated domains and tasks, and employs additional functionally powered by external services with which the system can interact.

Intelligent Automated Assistant

We present a statistical machine translation model that uses hierarchical phrases---phrases that contain subphrases. The model is formally a synchronous context-free grammar but is learned from a parallel text without any syntactic annotations. Thus it can be seen as combining fundamental ideas from both syntax-based translation and phrase-based translation. We describe our system's training and decoding methods in detail, and evaluate it for translation speed and translation accuracy. Using BLEU as a metric of translation accuracy, we find that our system performs significantly better than the Alignment Template System, a state-of-the-art phrase-based system.

Hierarchical Phrase-Based Translation

Some researchers have recently been calling attention to certain lasting “affordances” of paper documents over digital ones [21, 17]. Whereas the relationship between the two media is often assumed to be one of competition, in fact it is one of complementarity. While digital documents are dynamic (evolving in time), immaterial (made of informational substance), and agentive (capable of initiating actions), paper documents are:

Intelligent Paper

An identifiable sheet includes an area of sheet medium and, within the area, machine-readable markings that define two or more zones (202). The markings within the zones indicate a sheet identifier (208) identifying the identifiable sheet. The orientation of the sheet is given by an orientation marker (206). The position of the zones are given by markings (210) representing the zones position.

Cross-network functions via linked hardcopy and electronic documents

Automatic actions can be obtained through a network using an area of marking medium with machine-readable markings that encode an action/medium identifier. The action/medium identifier identifies an action that can be produced through the network, and also identifies the area of marking medium. For example, it may include a globally unique or network-wide page identifier as well as an action identifier that can be used to produce an action described by data associated with a counterpart digital page. Or it can include both a page identifier and a location identifier, with the location identifier also identifying an action that relates to the page's digital counterpart. Or it can include a document identifier and an action identifier. Or it can be a globally unique or network-wide sticker identifier that can be used to identify a document, a peripheral device, or another object to which the sticker is attached, and that also produces an action through the network.

Marking medium area with encoded identifier for producing action through network

We investigate the problem of predicting the quality of sentences produced by machine translation systems when reference translations are not available. The problem is addressed as a regression task and a method that takes into account the contribution of different features is proposed. We experiment with this method for translations produced by various MT systems and different language pairs, annotated with quality scores both automatically and manually. Results show that our method allows obtaining good estimates and that identifying a reduced set of relevant features plays an important role. The experiments also highlight a number of outstanding features that were consistently selected as the most relevant and could be used in different ways to improve MT performance or to enhance MT evaluation.

/pdf/estimating-the-sentence-level-quality-of-machine-translation-k26mlbkhi5.pdf

Estimating the Sentence-Level Quality of Machine Translation Systems

A system and method are provided which employ a neural network model which has been trained to predict a sequentialized form for an input text sequence. The sequentialized form includes a sequence of symbols. The neural network model includes an encoder which generates a representation of the input text sequence based on a representation of n-grams in the text sequence and a decoder which sequentially predicts a next symbol of the sequentialized form based on the representation and a predicted prefix of the sequentialized form. Given an input text sequence, a sequentialized form is predicted with the trained neural network model. The sequentialized form is converted to a structured form and information based on the structured form is output.

https://hal.inria.fr/hal-01623762/document

Marc Dymetman

Papers

Intelligent Paper

Cross-network functions via linked hardcopy and electronic documents

Marking medium area with encoded identifier for producing action through network

Estimating the Sentence-Level Quality of Machine Translation Systems

Sequence-based structured prediction for semantic parsing