Search results for "Cloud"

IT Technology Implications Analysis on the Occupational Risk: Cloud Computing Architecture

2014

Abstract The present paper is divided into three major areas: the analysis of occupational risk implications at national and international level, the European priorities in terms of occupational risk and the existing cloud computing services. Since human resource is present within each organization, it is required a comprehensive and actual assessment of the processes in which they participate. Like in any daily activity, processes and people contribute to the emergence of risks. If each organization creates healthy and safe workplaces that means that it contributes to the sustainable development of the area in which it operates. It can be said that occupational risk assessment and occupati…

Discovering and creating business opportunities for cloud services

2016

This study focuses on how the opportunities for cloud services are detected.The study develops a framework to detect and exploit cloud-based opportunities.This study incorporates entrepreneurship theories to extend and enrich IS research. Cloud computing provides new business opportunities for firms selling or using cloud services. However, little is known about how software firms detect and exploit these opportunities. Based on in-depth qualitative case studies, this study identified two different pathways followed by software firms when they detect and exploit opportunities. In the first pathway, the opportunity is based on an existing problem and need in the market. In the case firms, th…

A numerical model of the cloud-topped planetary boundary-layer: cloud processing of aerosol particles in marine stratus

1999

Abstract In a numerical study with the one-dimensional chemical microphysical stratus model CHEMISTRA the effect of stratiform clouds on aerosol particles is investigated. The microphysical part of CHEMISTRA consists of a detailed description of cloud microphysical processes by means of a joint two-dimensional particle distribution for aerosols and cloud droplets. In the chemical part of the model the particle spectrum is subdivided into three categories referring to inactivated aerosols, small and large cloud droplets. Aqueous phase chemical reactions are separately treated in the two droplet size classes. Numerical results are presented demonstrating that the uptake of trace gases by clou…

Estimation of Daily Solar Radiation from Measured Air Temperature Extremes in the Mid-Mediterranean Area

2012

AbstractDaily solar radiation Rs at ground level is a necessary input variable required for the evaluation of evapotranspiration and crop growth, development, and yield-simulation models. Nevertheless, it is measured in few weather stations and at many locations it is not observed; also, available Rs temporal series are generally no longer than a few years. A valid surrogate of Rs measurement is the diurnal air-temperature range (ΔT); indeed, ΔT is inversely proportional to cloudiness and therefore could be a good indicator of atmospheric transmittance. As opposed to Rs, daily maximum and minimum air temperatures are measured at many locations and their observations in developed countries b…

Evolutionary design optimization with Nash games and hybridized mesh/meshless methods in computational fluid dynamics

2012

Software Startup Practices -- Software Development in Startups through the Lens of the Essence Theory of Software Engineering

2020

Software startups continue to be important drivers of economy globally. As the initial investment required to found a new software company becomes smaller and smaller resulting from technological advances such as cloud technology, increasing numbers of new software startups are born. Typically, the main argument for studying software startups is that they differ from mature software organizations in various ways, thus making the findings of many existing studies not directly applicable to them. How, exactly, software startups really differ from other types of software organizations as an on-going debate. In this paper, we seek to better understand how software startups differ from mature so…

Cross-Sensor Adversarial Domain Adaptation of Landsat-8 and Proba-V images for Cloud Detection

2021

The number of Earth observation satellites carrying optical sensors with similar characteristics is constantly growing. Despite their similarities and the potential synergies among them, derived satellite products are often developed for each sensor independently. Differences in retrieved radiances lead to significant drops in accuracy, which hampers knowledge and information sharing across sensors. This is particularly harmful for machine learning algorithms, since gathering new ground truth data to train models for each sensor is costly and requires experienced manpower. In this work, we propose a domain adaptation transformation to reduce the statistical differences between images of two…

Pattern Recognition Scheme for Large-Scale Cloud Detection over Landmarks

2020

Landmark recognition and matching is a critical step in many Image Navigation and Registration (INR) models for geostationary satellite services, as well as to maintain the geometric quality assessment (GQA) in the instrument data processing chain of Earth observation satellites. Matching the landmark accurately is of paramount relevance, and the process can be strongly impacted by the cloud contamination of a given landmark. This paper introduces a complete pattern recognition methodology able to detect the presence of clouds over landmarks using Meteosat Second Generation (MSG) data. The methodology is based on the ensemble combination of dedicated support vector machines (SVMs) dependent…

A Deep Network Approach to Multitemporal Cloud Detection

2018

We present a deep learning model with temporal memory to detect clouds in image time series acquired by the Seviri imager mounted on the Meteosat Second Generation (MSG) satellite. The model provides pixel-level cloud maps with related confidence and propagates information in time via a recurrent neural network structure. With a single model, we are able to outline clouds along all year and during day and night with high accuracy.

Cloud detection machine learning algorithms for PROBA-V

2020

This paper presents the development and implementation of a cloud detection algorithm for Proba-V. Accurate and automatic detection of clouds in satellite scenes is a key issue for a wide range of remote sensing applications. With no accurate cloud masking, undetected clouds are one of the most significant sources of error in both sea and land cover biophysical parameter retrieval. The objective of the algorithms presented in this paper is to detect clouds accurately providing a cloud flag per pixel. For this purpose, the method exploits the information of Proba-V using statistical machine learning techniques to identify the clouds present in Proba-V products. The effectiveness of the propo…