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

In many monitoring and mapping applications, high-resolution data are required only in certain areas while others can receive lower attention. To this end, unmanned aerial vehicles (UAVs) can adjust the flight altitude to increase the resolution only where needed, making non-uniform coverage strategies efficient both in time and energy expenditure. In a multi-UAV monitoring context, it is necessary to deploy UAVs to inspect in parallel those areas where a higher resolution is required. To address this problem, we propose a decentralised deployment strategy inspired by the collective behaviour of honeybees. This strategy dynamically assigns UAVs to different areas to be monitored, and suitably re-assigns them to other areas when needed. We introduce an analytical macroscopic model of area monitoring from UAVs, and we propose a parameterisation that leads to an efficient allocation of UAVs to the areas to be monitored. We exploit abstract multi-agent simulations to study the dynamics of the deployment of UAVs to multiple areas, and we present results with simulations of a UAV swarm engaged in a weed monitoring and mapping task.

Dynamic UAV Swarm Deployment for Non-Uniform Coverage

Thanks to recent technological advances, there are now many potential applications for robotics including multi-agent systems. The aim of the RoboCare Project is to study issues and challenges involved in the design of systems for the care of the elderly that adopt both fixed and mobile heterogeneous agents. These agents can be robots, intelligent sensors or possibly even humans. RoboCare shares some aspects with other projects for the

The RoboCare project, cognitive systems for the care of the elderly

The activities of search and rescue of victims in large-scale disasters are very relevant social problems, and from a scientific viewpoint raise many different technical problems in the fields of artificial intelligence, robotics and multi agent systems. In this paper we describe the development of a multi agent system based on the RoboCup Rescue simulator to allow monitoring and decision support, that are needed in a rescue operation. Two significant accomplishments are reported in this paper: the first is a framework for cognitive agent development that provides for the capabilities of information fusion, planning and coordination; the second one is a methodology for evaluation of multi-agent systems in this scenario that aims at measuring not only the efficiency of a system, but also its robustness when conditions in the environment change.

/pdf/design-and-evaluation-of-multi-agent-systems-for-rescue-uvpmtfgibb.pdf

Design and evaluation of multi agent systems for rescue operations

As robots are expected to become more and more available in everyday environments, interaction with humans is assuming a central role. Robots working in populated environments are thus expected to demonstrate socially acceptable behaviors and to follow social norms. However, most of the recent works in this field do not address the problem of explicit representation of the social norms and their integration in the reasoning and the execution components of a cognitive robot. In this paper, we address the design of robotic systems that support some social behavior by implementing social norms. We present a framework for planning and execution of social plans, in which social norms are described in a domain and language independent form. A full implementation of the proposed framework is described and tested in a realistic scenario with non-expert and non-recruited users.

Explicit representation of social norms for social robots

Precision agriculture represents a very promising domain for swarm robotics, as it deals with expansive fields and tasks that can be parallelised and executed with a collaborative approach. Weed monitoring and mapping is one such problem, and solutions have been proposed that exploit swarms of unmanned aerial vehicles (UAVs). With this paper, we move one step forward towards the deployment of UAV swarms in the field. We present the implementation of a collective behaviour for weed monitoring and mapping, which takes into account all the processes to be run onboard, including machine vision and collision avoidance. We present simulation results to evaluate the efficiency of the proposed system once that such processes are considered, and we also run hardware-in-the-loop simulations which provide a precise profiling of all the system components, a necessary step before final deployment in the field.

Daniele Nardi

Papers

Dynamic UAV Swarm Deployment for Non-Uniform Coverage

The RoboCare project, cognitive systems for the care of the elderly

Design and evaluation of multi agent systems for rescue operations

Explicit representation of social norms for social robots

Field Coverage for Weed Mapping: Toward Experiments with a UAV Swarm