다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

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

“Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks”の学習報告

https://www.cs.ox.ac.uk/people/bernardo.cuencagrau/publications/PelletDemo.pdf

Pellet: A practical OWL-DL reasoner

Data integration is the problem of combining data residing at different sources, and providing the user with a unified view of these data. The problem of designing data integration systems is important in current real world applications, and is characterized by a number of issues that are interesting from a theoretical point of view. This document presents on overview of the material to be presented in a tutorial on data integration. The tutorial is focused on some of the theoretical issues that are relevant for data integration. Special attention will be devoted to the following aspects: modeling a data integration application, processing queries in data integration, dealing with inconsistent data sources, and reasoning on queries.

/pdf/data-integration-a-theoretical-perspective-58aesjvhuk.pdf

Data integration: a theoretical perspective

Multi Robot Systems are, nowadays, an important research area within Robotics and Artificial Intelligence. Although Multi Robot Systems can be regarded as a particular case of Multi Agent Systems, it seems appropriate to study the Multi Robot Systems from a specific viewpoint, because of the issues which arise from the embodiment of agents operating in real environments. In this paper, we present an analysis of Multi Robot Systems by looking at their cooperative aspects. In particular, we propose a taxonomy of Multi Robot Systems and a characterization of reactive and social deliberative behaviors of the Multi Robot System as a whole. Finally, we address some Multi Robot Systems, which we consider representative of the various nodes in our taxonomy.

/pdf/reactivity-and-deliberation-a-survey-on-multi-robot-systems-43rvodlhvs.pdf

Reactivity and Deliberation: A Survey on Multi-Robot Systems

We present two concept languages, called PL1 and PL2 which are extensions of TC. We prove that the subsumption problem in these languages can be solved in polynomial time. Both languages include a construct for expressing inverse roles, which has not been considered up to now in tractable languages. In addition, PL1 includes number restrictions and negation of primitive concepts, while Pl2 includes role conjunction and role chaining.

By exploiting recent complexity results, we show that none of the constructs usually considered in concept languages can be added to PL1 and PL2 without losing tractabtlity. Therefore, on the assumption that Languages are characterized by the set of constructs they provide, the two languages presented in this paper provide a solution to the problem of singling out an optimal trade-off between expressive power and computational complexity.

/pdf/tractable-concept-languages-4zikmdog9p.pdf

Tractable concept languages

Programming the behavior of multi-robot systems is a challenging task which has a key role in developing effective systems in many application domains. In this paper, we present Petri Net Plans (PNPs), a language based on Petri Nets (PNs), which allows for intuitive and effective robot and multi-robot behavior design. PNPs are very expressive and support a rich set of features that are critical to develop robotic applications, including sensing, interrupts and concurrency. As a central feature, PNPs allow for a formal analysis of plans based on standard PN tools. Moreover, PNPs are suitable for modeling multi-robot systems and the developed behaviors can be executed in a distributed setting, while preserving the properties of the modeled system. PNPs have been deployed in several robotic platforms in different application domains. In this paper, we report three case studies, which address complex single robot plans, coordination and collaboration.

https://www.dis.uniroma1.it/~iocchi/publications/iocchi-moca06.pdf

Petri Net Plans

/pdf/reasoning-in-expressive-description-logics-2lodsa7g5l.pdf

Reasoning in expressive description logics

In this paper we present a perception system for agriculture robotics that enables an unmanned ground vehicle (UGV) equipped with a multi spectral camera to automatically perform the crop/weed detection and classification tasks in real-time. Our approach exploits a pipeline that includes two different convolutional neural networks (CNNs) applied to the input RGB+near infra-red (NIR) images. A lightweight CNN is used to perform a fast and robust, pixel-wise, binary image segmentation, in order to extract the pixels that represent projections of 3D points that belong to green vegetation. A deeper CNN is then used to classify the extracted pixels between the crop and weed classes. A further important contribution of this work is a novel unsupervised dataset summarization algorithm that automatically selects from a large dataset the most informative subsets that better describe the original one. This enables to streamline and speed-up the manual dataset labeling process, otherwise extremely time consuming, while preserving good classification performance. Experiments performed on different datasets taken from a real farm robot confirm the effectiveness of our approach.

/pdf/fast-and-accurate-crop-and-weed-identification-with-4atpe3z3yd.pdf

Daniele Nardi

Papers

Reactivity and Deliberation: A Survey on Multi-Robot Systems

Tractable concept languages

Petri Net Plans

Reasoning in expressive description logics

Fast and Accurate Crop and Weed Identification with Summarized Train Sets for Precision Agriculture