The Galicia HF Experience: Analysis of the Results of the SeaSonde HF Radar Experience in Galicia

Two long-range CODAROS SeaSonde HF radar stations were installed and operated for three months (Nov 2005 to Feb 2006) in the Galician coast, the main area affected by the Prestige disaster. During this period, all the produced data were freely distributed in real time via Internet. The dissemination system was fully integrated with the Puertos del Estado web products, which are providing real time data of several oceanographic and atmospheric parameters, such as sea level and waves. One of the buoys of the Puertos del Estado deep-water network, equipped with a current meter, is moored in the area covered by the Radar system. Analysis of the three months of data shows good correlation between both sources of information (RMS of 5.11 cm/s for u component and 6.67 cm/s for ν) [1]. Additionally, a lagrangian buoy was released in the area, in order to analyze the benefit of employing HF radar currents for the tracking of drifting objects. The validation exercise with the drifting buoy was carried out inside the ESEOO project; the analysis was lead by University of Cantabria and Imedea balear, as part of their modeling tasks inside ESEOO, and the drifting buoy was released by SASEMAR, the Spanish Coastguard, as part of an ESEOO exercise [2]. A particle model was employed with and without the use of HF radar currents. Results of the experiment clearly show a positive impact of the use of measured current. When using HF data, the search and rescue areas are reduced, in average, in 49%. In this work, results from this experience will be analyzed in detail, making special focus in the scientific aspects of the comparison with the moored and drifting buoys.

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Diagnostics and Prognostics of Energy Conversion Processes via Knowledge-Based Systems

Proceedings ◽

10.3390/wef-06937 ◽

2020 ◽

Vol 58 (1) ◽

pp. 1

Author(s):

Roberto Melli ◽

Enrico Sciubba

Keyword(s):

Expert System ◽

Knowledge Base ◽

Real Time ◽

System Analysis ◽

Intelligent System ◽

Time Derivative ◽

Time History ◽

Control Procedure ◽

Time Data ◽

Ongoing Research

This paper presents a critical and analytical description of an ongoing research program aimed at the implementation of an expert system capable of monitoring, through an Intelligent Health Control procedure, the instantaneous performance of a cogeneration plant. The expert system is implemented in the CLIPS environment and is denominated PROMISA as the acronym for Prognostic Module for Intelligent System Analysis. It generates, in real time and in a form directly useful to the plant manager, information on the existence and severity of faults, forecasts on the future time history of both detected and likely faults, and suggestions on how to control the problem. The expert procedure, working where and if necessary with the support of a process simulator, derives from the available real-time data a list of selected performance indicators for each plant component. For a set of faults, pre-defined with the help of the plant operator (Domain Expert), proper rules are defined in order to establish whether the component is working correctly; in several instances, since one single failure (symptom) can originate from more than one fault (cause), complex sets of rules expressing the combination of multiple indices have been introduced in the knowledge base as well. Creeping faults are detected by analyzing the trend of the variation of an indicator over a pre-assigned interval of time. Whenever the value of this ‘‘discrete time derivative’’ becomes ‘‘high’’ with respect to a specified limit value, a ‘‘latent creeping fault’’ condition is prognosticated. The expert system architecture is based on an object-oriented paradigm. The knowledge base (facts and rules) is clustered—the chunks of knowledge pertain to individual components. A graphic user interface (GUI) allows the user to interrogate PROMISA about its rules, procedures, classes and objects, and about its inference path. The paper also presents the results of some simulation tests.

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How Can Existing Ground-Based Profiling Instruments Improve European Weather Forecasts?

Bulletin of the American Meteorological Society ◽

10.1175/bams-d-17-0231.1 ◽

2019 ◽

Vol 100 (4) ◽

pp. 605-619 ◽

Cited By ~ 14

Author(s):

A. J. Illingworth ◽

D. Cimini ◽

A. Haefele ◽

M. Haeffelin ◽

M. Hervo ◽

...

Keyword(s):

Real Time ◽

Traffic Control ◽

Positive Impact ◽

Weather Forecast ◽

Weather Conditions ◽

Time Data ◽

Weather Forecasts ◽

Forecast Models ◽

Wind Lidar ◽

Microwave Radiometers

Abstract To realize the promise of improved predictions of hazardous weather such as flash floods, wind storms, fog, and poor air quality from high-resolution mesoscale models, the forecast models must be initialized with an accurate representation of the current state of the atmosphere, but the lowest few kilometers are hardly accessible by satellite, especially in dynamically active conditions. We report on recent European developments in the exploitation of existing ground-based profiling instruments so that they are networked and able to send data in real time to forecast centers. The three classes of instruments are i) automatic lidars and ceilometers providing backscatter profiles of clouds, aerosols, dust, fog, and volcanic ash, the last two being especially important for air traffic control; ii) Doppler wind lidars deriving profiles of wind, turbulence, wind shear, wind gusts, and low-level jets; and iii) microwave radiometers estimating profiles of temperature and humidity in nearly all weather conditions. The project includes collaboration from 22 European countries and 15 European national weather services, which involves the implementation of common operating procedures, instrument calibrations, data formats, and retrieval algorithms. Currently, data from 265 ceilometers in 19 countries are being distributed in near–real time to national weather forecast centers; this should soon rise to many hundreds. One wind lidar is currently delivering real time data rising to 5 by the end of 2019, and the plan is to incorporate radiometers in 2020. Initial data assimilation tests indicate a positive impact of the new data.

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SPATIAL DATA INTEGRATION USING ONTOLOGY-BASED APPROACH

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xl-1-w5-293-2015 ◽

2015 ◽

Vol XL-1-W5 ◽

pp. 293-296 ◽

Cited By ~ 9

Author(s):

S. Hasani ◽

A. Sadeghi-Niaraki ◽

M. Jelokhani-Niaraki

Keyword(s):

Data Integration ◽

Real Time ◽

Spatial Data ◽

Service Oriented Architecture ◽

Low Cost ◽

Time Integration ◽

Semantic Heterogeneity ◽

Sources Of Information ◽

Time Data ◽

Service Oriented

In today's world, the necessity for spatial data for various organizations is becoming so crucial that many of these organizations have begun to produce spatial data for that purpose. In some circumstances, the need to obtain real time integrated data requires sustainable mechanism to process real-time integration. Case in point, the disater management situations that requires obtaining real time data from various sources of information. One of the problematic challenges in the mentioned situation is the high degree of heterogeneity between different organizations data. To solve this issue, we introduce an ontology-based method to provide sharing and integration capabilities for the existing databases. In addition to resolving semantic heterogeneity, better access to information is also provided by our proposed method. Our approach is consisted of three steps, the first step is identification of the object in a relational database, then the semantic relationships between them are modelled and subsequently, the ontology of each database is created. In a second step, the relative ontology will be inserted into the database and the relationship of each class of ontology will be inserted into the new created column in database tables. Last step is consisted of a platform based on service-oriented architecture, which allows integration of data. This is done by using the concept of ontology mapping. The proposed approach, in addition to being fast and low cost, makes the process of data integration easy and the data remains unchanged and thus takes advantage of the legacy application provided.

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On-Line Power System Analysis Based on Hybrid Network Model

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.484-485.665 ◽

2014 ◽

Vol 484-485 ◽

pp. 665-670

Author(s):

Qin Xiao

Keyword(s):

Power System ◽

Electric Power ◽

Real Time ◽

Network Model ◽

System Analysis ◽

Hybrid Network ◽

Time Data ◽

System Operation ◽

Power System Operation ◽

Power System Analysis

Online power system analysis to electric mode-based on information that will offer a decided in real time the quality of the studies and efficiency of the power system operation precision closely associated with the power system model. Accurate and quick decision based on real-time data analysis needs battle plan deregulation of the power system in all over the world. In addition a significant expansion of electric power system in India in recent times, especially in the 2003 introduction of electricity bill, introduction of open access, electric power market, the appearance of communication through power with complex power system operation and control. Electric power network analysis in real-time data is expected to further improve the critical role of power network operation to repair the proposed law after transmission loss of tariff and share. All this forced the power system real time is accurate, but conditions analysis based on different principles. In order to meet the requirements of all, from the monitoring, commercial, reliability and stability of the Angle, attempt to have been forced to take hybrid network model in natural real-time supervisory control and data acquisition (SCADA) systems work so far a single network model of the integrated. This paper presents a network model for the theory foundation and the same is in the southern area rapidly adapt to load center (SRLDC) Bangalore and utilization of energy management system in India (EMS) real-time systems and tools. It is proved to be how to planning can online network system modeling and analysis of relatively simple in complex operational requirements. The experimental results show that the online power management strategy to adapt to can be a key tool control engineers hand in complex power system operation situations.

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Ambulatory Assessment

European Psychologist ◽

10.1027/1016-9040.14.2.109 ◽

2009 ◽

Vol 14 (2) ◽

pp. 109-119 ◽

Cited By ~ 66

Author(s):

Ulrich W. Ebner-Priemer ◽

Timothy J. Trull

Keyword(s):

Real Time ◽

Clinical Psychology ◽

Real Life ◽

Ambulatory Assessment ◽

Computer Assisted ◽

Affective Valence ◽

Time Data ◽

Physiological Processes ◽

Context Specific ◽

Questionnaire Studies

Convergent experimental data, autobiographical studies, and investigations on daily life have all demonstrated that gathering information retrospectively is a highly dubious methodology. Retrospection is subject to multiple systematic distortions (i.e., affective valence effect, mood congruent memory effect, duration neglect; peak end rule) as it is based on (often biased) storage and recollection of memories of the original experience or the behavior that are of interest. The method of choice to circumvent these biases is the use of electronic diaries to collect self-reported symptoms, behaviors, or physiological processes in real time. Different terms have been used for this kind of methodology: ambulatory assessment, ecological momentary assessment, experience sampling method, and real-time data capture. Even though the terms differ, they have in common the use of computer-assisted methodology to assess self-reported symptoms, behaviors, or physiological processes, while the participant undergoes normal daily activities. In this review we discuss the main features and advantages of ambulatory assessment regarding clinical psychology and psychiatry: (a) the use of realtime assessment to circumvent biased recollection, (b) assessment in real life to enhance generalizability, (c) repeated assessment to investigate within person processes, (d) multimodal assessment, including psychological, physiological and behavioral data, (e) the opportunity to assess and investigate context-specific relationships, and (f) the possibility of giving feedback in real time. Using prototypic examples from the literature of clinical psychology and psychiatry, we demonstrate that ambulatory assessment can answer specific research questions better than laboratory or questionnaire studies.

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