Java Applications Research Papers

Remote Class Prefetching: Improving Performance of Java Applications on Grid Platforms

2024, Lecture Notes in Computer Science

In this paper we introduce and evaluate two prefetching techniques to improve the performance of Java applications executed on the grid. These techniques are experimentally evaluated on two grid environments, by running test applications... more

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Artificial Satellites. Meteorological Satellites

by Sorin Bostan

2023, pesd.ro

Abstract. The importance of the satellite in various fields of activity has triggered its continous improvement, having as a result the emergence of more and more varied products and the increase of the resolution of other products.... more

Fig. 1 - Spinning Enhanced Visible and Infrared Imager Since 2000 and until now, both geostationary and polar satellites have beer launched. We shall consider here three satellites: MSG 1 (Meteosat Second Generation), METOP-A and Jason 2.

Fig. 2 - The display of instruments on the board of METOP-A satellite

Fig. 3 - Area with a high ammonia concentration

In October 2006, the first of the three satellites for the Polar System EUMETSAT (EPS) was launched from the Baikonur Cosmodrome in Kazakhstan. Once it entered the orbit, the satellite took the name of METOP-A. It is provided with exceptional equipments, among which we emphasize (see Fig.2) IASI (Infrared Atmospheric Sounding Interferometer), GOME-2 (Global Ozone Monitoring Experiment), and MHS (Microwave Humidity Sounder).

Fig. 5 - Dean Hurricane in the Gulf of Mexico on the 20" of August 2007 GOME-2 is a device installed on board of the polar satellite METOP-A, by eans of which the sulfur dioxide (SO) emitted of the Mount Redoubt volcano in

from the background noise of the device. By filtering and data gathering during one year of continuous observations (more than one million IASI soundings per day, 10-20 per cent of which are for ammonia observations), the researchers were able to obtain maps of ammonia concentration (Fig. 3) and compare them to recent atmospheric models. This work has highlighted an underestimation of ammonia sources provided by the current inventory for agricultural valleys of the Northern hemisphere, particularly in America (e.g. San Joaquin in California and Snake River Valley in Idaho) and Europe (Po and Ebro valleys in Italy and Spain, respectively). The most significant differences were found in Central Asia, where some sources that do not exist in current inventories were identified.

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MetPy: A Meteorological Python Library for Data Analysis and Visualization

by Kevin Goebbert

2023, Bulletin of the American Meteorological Society

MetPy is an open-source, Python-based package for meteorology, providing domain-specific functionality built extensively on top of the robust scientific Python software stack, which includes libraries like NumPy, SciPy, Matplotlib, and... more

Fig. 2. Map of the continental United States with background GOES-16 channel 02 imagery valid 1926 UTC 27 Jun 2022, overlayed with contours of equivalent potential temperature calculated from Real-Time Mesoscale Analysis (RTMA) output and station models of surface observations from a collection of surface observation METARs. While the netCDF data model and data stored in netCDF format are core to the design of MetPy and its interoperability with other tools, meteorological and atmospheric data are often stored in domain-specific formats. This is especially true when it comes to historical archives, which are crucial for many education and research applications. To facilitate the use of these data in Python, MetPy has support for many important domain-specific formats for data, including NEXRAD level 2, NEXRAD level 3, GINI, METAR, and GEMPAK. Reading data in these formats produces a pandas DataFrame or an xarray Dataset as appropriate;

Fig. 3. Vertical cross section of relative humidity (shaded; dimensionless), potential temperature (contours; K), and wind components (barbs; kt) tangential and normal to the plane of the cross section. Latitude, longitude coordinates along the cross-section path are provided along the x axis; vertical pressure levels are provided along the y axis. The top-left corner inset is a map of the trace of the cross section and contours of 500-hPa geopotential height. Data from North American Regional Reanalysis (NARR) valid 1800 UTC 4 Apr 1987.

Fig. 4. Example Python code to produce Fig. 5. (left) Manual creation of figure and map through Matplotlib and Cartopy. (right) Simplified code using MetPy’s declarative plotting syntax.

Fig. 5. Geopotential heights (contoured; m), wind speed (filled contours; kt), and wind barbs (kt) from Global Forecast System output valid at 1200 UTC 31 Oct 2010. Example analysis produced using MetPy’s declarative plotting syntax demonstrated in Fig. 4.

Fig. 6. NOAA/NWS/Storm Prediction Center (SPC) 1200 UTC 17 Mar 2021 Day 1 Convective Outlook recreated using MetPy’s declarative plotting interface. Data from SPC GeoJSON archive.

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Profiling heliophysics data in the pythonic cloud

by Alex Antunes

2023, Frontiers in Astronomy and Space Sciences

Analysis of long timespan heliophysics and space physics data or application of machine learning algorithms can require access to petabyte-scale and larger data sets and sufficient computational capacity to process such “big data”. We... more

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Nutrition Education for Care and Support of Tuberculosis Patients

by Dr. Gurjeet Kaur Chawla

2023, International Journal for Research in Applied Science and Engineering Technology

Tuberculosis is one of the most fatal disease in the world, in human caused mostly "by the gram-positive acid-fast bacilli under the genus mycobacterium. The relation between tuberculosis and undernutrition has long been known. In this... more

TABLE 4.1 Demographic table This table depicts that 60% of patients were below the age of 40 while 40% were above the age of 40 and mean and S.D. for the same 1s 38.56+7.43. Out of 30 patients 74% belonged to the Lower income group and the rest 26% belonged to Middle income group while there was none from higher income group the mean and S.D. turned out to be 1.16+0.37. Out of 30 patients 77% patients had a family income below Rs. 1,00,000 and the other 26% had family income between Rs. 1,00,000 to 10,00,000 per annum, so the mean and S.D. were 1.26+0.45 .

TABLE 4.2 Physical Activity Pattern This table depicts that out of 30 patients 50% are moderate workers while 46% are heavy workers and the rest 4% are sedentary. On the basis of physical activity pattern only 36 patients do physical workout regularly and rest don’t

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Remote Class Prefetching: Improving Performance of Java Applications on Grid Platforms

by carlos enrique mendoza figueira

2023, Lecture Notes in Computer Science

In this paper we introduce and evaluate two prefetching techniques to improve the performance of Java applications executed on the grid. These techniques are experimentally evaluated on two grid environments, by running test applications... more

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Development of a Complex Geospatial/RF Design Model in Support of Service Volume Engineering Design

by Siiahram Sarkani Ph D P E

2022, International Journal of Interdisciplinary Telecommunications and Networking

Today’s National Airspace System (NAS) is managed using an aging surveillance radar system. The radar technology is not adequate to sustain the support of aviation growth and cannot be adapted to use 21st century technologies Therefore,... more

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Adopting the Hadoop Architecture to Process Satellite Pollution Big Data

by Chaker El Amrani

2022, International Journal of Technology and Engineering Studies

This research aims to monitor abnormal climate changes and supervise Air Quality (AQ), especially in Morocco. This study aims to contribute to finding a solution to the AQ degradation and climate change issues by using Remote Sensing (RS)... more

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Hadoop Paradigm for Satellite Environmental Big Data Processing

by Chaker El Amrani

2022, International Journal of Agricultural and Environmental Information Systems

The important growth of industrial, transport, and agriculture activities, has not led only to the air quality and climate changes issues, but also to the increase of the potential natural disasters. The emission of harmful gases,... more

Figure 8. A screenshot of the Raspberry PI measured values

Figure | exp nicrowave passing through atmospheric layers, afterward, and reflected energy by the measured . Then, values are transmitted to the ground stations to be converted into raster arget is recorded ains the mechanism of satellite sensors, in resume, instruments emit the EME li mages, map or scientific data files. Table 6 summarizes the most used sensors in this research, t najority of these Level 2 Data, 20 TROPOMI, TAN sensors are active sounders like: the AMSU, IASI (BUFR Descriptors for IA 7), MHS, MLS and AIRS. There are also some active spectrometers such as t SO-FTS, MODIS, MIRS and the GOME-2 (Rosemary, 2016). The SPR of t Ke he SI he he iforementioned sensors ranges between high to low. In addition, all of these satellite sensors have a igh TPR feeding from one to two days. 6. METHOD Table 5. Passive satellites sensors feature

Figure 5. Used RS data sources and Information Services Center (GESDISC). We have collected RS data also from other federal agencies providing free and NRT RS data such as the Infusing Satellite Data into Environmental Applications (NESDIS) of NOAA (“NOAA National Environmental Satellite, Data, and Information Service (NESDIS) |,” 2018). Moreover, we have acquired RS data from the Copernicus platform built by ESA. We have gathered also data from some Meteorological Ground Station (MGS) through these websites: www.weatherunderground.com and www.worldweatheronline.com in order to apply a data validation. In addition, we have developed a Raspberry PI robot, equipped with MQ sensors in order to support RS data validation. Figure 5 shows the different data sources with their satellites, instruments and their products details. Table 7 contains the Unified Resources Locator (URLs) of the used satellites data sources.

density of pollutant gases in the ground area. The obtained values from the robot are unit less. Consequently, we have used some mathematical equations to convert them into the Part per Million (PPM) unit. Finally, all the measured data are stored into a remote relational database to be exploited after in NRT.

7.3. The Velocity of RS Data * Velocity assigns to the rate of which data come, and how fast must be processed, by the age of Internet and the wide range of using satellites sensors and IOT, a rapid processing must be achieved to deduce useful deep insights in NRT, heling in decision making. Velocity varies in function of data category. There are two kind of data processing: the NRT or streaming data and the batch data. Streaming data are treated as soon as possible in order to keep potential value and data freshness. Moreover, data arrive continuously occurring enormous volumes (Sun et al., 2016). However, batch data are stored in chunks within a specified, finite size and their processing takes a long time, and it needs multiple Central Processing Unit (CPU) and memories (Russom, 2011). Figure 11 shows the MDEO, NASA, NOAA and ESA RSBD velocity. We notice an important daily number of files coming with a big size. For instance, the Suomi National Polar-orbiting Partnership (NPP) satellite provides data of the OMPS sensors with a high rate reaching two thousand file per day, EPS-Africa channel, provides about four thousand files daily, the Sentinel-5P affords also a huge daily data encompassing forty-eight GB. Similarly, the NASA and NOAA data have also an important velocity, see Figure 10 and 11. Thus, RSBD come in NRT, MDEO data are available with a frequency and latency of thirty minutes (Min). However, the NASA data have a frequency of five Min and two hours of latency. As a result, RSBD are regarded as batch datasets, because, they need a big capacity of storage, CPU and memories to be processed. Figure 12 displays the daily size of RS data. Brom the aforementioned ctatistical reculte and from the attrihite definition hased in the four

Figure 15. The input and output of the RS ingestion layer

our research, this layer will contain some novel algorithms helping in data optimization, validation and interpolation. Furthermore, it will contain a prediction software based in Artificial Intelligent (AD algorithms helping in decision-making concerning the AQ and climate changes issues. Figure 17 illustrates the general architecture of the MapReduce formwork that will be exploited to process the stored data. A MapReduce program is composed of a map procedure which performs filtering and sorting (such as sorting the temperature by latitude, longitude and time into queues), and a reduce function, which performs a summary operation (such as calculating the average temperature in each queue). In our research MapReduce will be used mainly to enhance the quality of satellite data, interpolating, fusing and validating remote sensing data and finally applying some AI model to predict climate changes and pollution data.

Figure 17. The general architecture of the MapReduce

Figure 19. VMR of CO (PPMv) Table 9. Comparison among related works

Table 1. Some related works and their focusing

Table 6. Used satellites sensors specifications Jefinitions concern also RSBD. On the other hand, RS data are becoming more widely used from listinctive fields (e.g., environmental monitoring, climate forecasting, and scientific researches), by he advanced of satellites, sensors, the RS is undergoing an explosive growth (Ma et al., 2015). This advances in sensors technologies have given rise also, to the increase of the complexity of RS data, particularly the diversity and the dimensionality. Furthermore, the large scale environmental are >xploiting regional to global covered temporal and multi sensors RS data for processing. Moreover, RS technique deals with a large collection of datasets with a huge volume. So, the first definition is nore suitable to describe RSBD. In the next subsection, we will discuss several aspects and features of the used RSBD, the diversity of data sources, and their huge volume, complexity and velocity.

NOAA, the Copernicus platform built and operated by ESA, the MGS and the Raspberry PI robot sensors data. The role of this layer is to automatically connect with many File Transfer Protocol (FTP) or Hypertext Transfer Protocol (HTTPS) protocols using the WGET and CURL, doing the authentication, selecting the interesting channels and products to be downloaded and finally making data available in NRT to be preprocessed.

developed a distributed architecture based in the Hadoop paradigm. Accordingly, the processing is scalable and optimized.

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Porting the WRF Model to EumedGrid and Simulation of Air Quality in Urban Zones

by Chaker El Amrani

2022, Proceedings of The International Symposium on Grids and Clouds (ISGC) 2012 — PoS(ISGC 2012)

The Weather Research and Forecast (WRF) is a specific program for forecasting and research. WRF processing is composed of three steps: pre-processing, core model execution and postprocessing. WRF/Chem is the WRF coupled with Chemistry.... more

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Towards Remote Sensing Datasets Collection and Processing

by Chaker El Amrani

2022, International Journal of Embedded and Real-Time Communication Systems

The world is witnessing important increases in industrial, transport and agriculture activities. This leads to economic growth, but, on the other hand, causes substantial damage in urban air, due to emissions of harmful gases, mainly CO,... more

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বায়ুদূষণ রোধে আদালত

by Ain o Salish Kendra (ASK)

2022, Bulletin March

রাজধানী ঢাকা বর্তমানে ১৬ মিলিয়ন লোকের আবাসস্থল। এক সময়ের প্রাচ্যের ভেনিস খ্যাত এ নগরী আজ বিশ্বের সবচেয়ে বসবাস-অযোগ্য নগরী হিসেবে পরিচিতি পেয়েছে। সাম্প্রতিককালের চরম মাত্রার বায়ুদূষণ এ নগরীর ১৬ মিলিয়ন মানুষের জীবনকে দুর্বিষহ করে তুলেছে।... more

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Network support for integrated design

by Daizhong Su

2022, Integrated Manufacturing Systems

A framework of network support for utilization of integrated design over the Internet has been developed. The techniques presented are also applicable for intranet/extranet. The integrated design system was initially developed for local... more

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Adopting the Hadoop Architecture to Process Satellite Pollution Big Data

by Badr-Eddine Boudriki Semlali

2022, International Journal of Technology and Engineering Studies

This research aims to monitor abnormal climate changes and supervise Air Quality (AQ), especially in Morocco. This study aims to contribute to finding a solution to the AQ degradation and climate change issues by using Remote Sensing (RS)... more

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A Stream Processing Software for Air Quality Satellite Datasets

by Badr-Eddine Boudriki Semlali

2022

There is no doubt that air pollution harms human health. Municipal areas are the most affected by the degradation of the air quality by discharging anthropogenic gases from transport and industrial activities. This research collected... more

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Open Programmable Architecture for Java-enabled Network Devices

by Tal Lavian

2021

1 Overview Current network devices enable connectivity between end systems given a set of protocol software bundled with vendor hardware. It is impossible for customers to add software functionality running locally on top of network... more

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Air2Day: An Air Quality Monitoring Adviser in Morocco

by Mohamed Akram

2021, International Journal of Computer Applications

This article aims to present an end-to-end software solution capable of providing up to date weather and pollution values and health recommendations based on User profiles and personal health data, while making use of environmental... more

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MetOp Satellites Data Processing for Air Pollution Monitoring in Morocco

by Chaker El Amrani

2021, International Journal of Electrical and Computer Engineering (IJECE)

This paper presents a data processing system based on an architecture comprised of multiple stacked layers of computational processes that transforms Raw Binary Pollution Data coming directly from Two EUMETSAT MetOp satellites to our... more

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A Study of Information Content of As-Built Drawings for USAA

by Mark Clayton

2021, Retrieved January 14, …

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SAT-CEP-monitor: An air quality monitoring software architecture combining complex event processing with satellite remote sensing

by Badr-Eddine Boudriki Semlali

2021, Computers and Electrical Engineering

Air pollution is a major problem today that causes serious damage to human health. Urban areas are the most affected by the degradation of air quality caused by anthropogenic gas emissions. Although there are multiple proposals for air... more

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Satellite Big Data Ingestion for Environmentally Sustainable Development

by Badr-Eddine Boudriki Semlali

2021

Currently, many environmental applications take advantage of remote sensing techniques, particularly air quality monitoring, climate changes overseeing, and natural disasters prediction. However, a massive volume of remote sensing data is... more

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MetOp Satellites Data Processing for Air Pollution Monitoring in Morocco

by International Journal of Electrical and Computer Engineering (IJECE)

2020, International Journal of Electrical and Computer Engineering (IJECE)

This paper presents a data processing system based on an architecture comprised of multiple stacked layers of computational processes that transforms Raw Binary Pollution Data coming directly from Two EUMETSAT MetOp satellites to our... more

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Development of a Java-based application for environmental remote sensing data processing

by International Journal of Electrical and Computer Engineering (IJECE) and

2020, International Journal of Electrical and Computer Engineering (IJECE)

Air pollution is one of the most serious problems the world faces today. It is highly necessary to monitor pollutants in real-time to anticipate and reduce damages caused in several fields of activities. Likewise, it is necessary to... more

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Open Java-Based Intelligent Agent Architecture for Adaptive Networking Devices

by Tal Lavian

2020

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Open Programmable Architecture for Java-enabled Network Devices

by Tal Lavian

2020

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Adopting the Hadoop Architecture to Process Satellite Pollution Big Data

by Badr-Eddine Boudriki Semlali and

2020, International Journal of Technology and Engineering Studies

The important growth of industrial, transport and agriculture activities, has not led only to the Air Quality (AQ) and climate changes issues, but also to the increase of the potential natural disasters. The emission of harmful gases, in... more

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SAT-ETL-Integrator: an extract-transform-load software for satellite big data ingestion

by Badr-Eddine Boudriki Semlali

2020, Journal of Applied Remote Sensing

Satellite data are used in several environmental applications, particularly in air quality supervising, climate change monitoring, and natural disaster predictions. However, remote sensing (RS) data occur in huge volume, in near-real... more

Fig. 3 Layered architecture of RSBD system.

Fig. 4 The proposed BD architecture to process RSBD.

Fig. 5 The input, output, and the database of the ingestion layer script.

Fig. 6 The conceptual model of data of the ingestion layer database.

Fig. 7 The paradigm of the ingestion layer.

Fig. 8 (a) The daily size of data (MB) before and after the decompression step. (b) The daily number of files before and after the decompression step.

Fig. 10 The MetOp A trace orbit from IXION tool. the aforementioned results. We have developed another shell script to filter files by orbit cross- ing based on the hour of scan (see Fig. 26). The script extracts the time of crossing from the name of file. Figures | 1(a) and 11(b) show, respectively, the number of files and the size (MB) after the orbit filter operation.

Fig. 11 (a) The daily number of files after orbit filter. (b) The daily size (MB) of files after orbit filter.

Fig. 13 The granule subsetting of Morocco."

Fig. 14 (a) The daily number of files after the subsetting step. (b) The daily size of data (GB) after the subsetting step.

Fig. 15 (a) Daily average number of plots versus the scanned surface (km?). (b) Daily subset size (GB) versus the scanned surface (km7?).

Fig. 16 A snapshot of the HDF5 variables file using the Panoply software

Fig. 17 A snapshot of the BUFR variables file using the BUFRExtract software.

Fig. 18 The flowchart of the RSBD exctraction.

Fig. 19 The average daily plots after the extraction step.

Fig. 20 The total daily size of the RSBD (GB) during the processing in the ingestion layer.

Fig. 21 Time execution of the RSBD (min) during the processing in the ingestion layer.

Fig. 22 The total daily number of plots during the extraction step.

Fig. 23 The final CSV output of the SAT-ETL-integrator software contaning the VCD of COs ir Morocco (PPMm).

Fig. 25 BASH code to decompress the RS files.

Table 1 Sources channel and characteristics of the used satellite data in the case study.

Table 3 Satellite orbits crossing is period. Fig. 9 The BUFR file is nomination.

Table 4 RS data conversion specifications.

Note: Vel, velocity; H, hardware; A, architecture; T, time; V, validation; F, fusion; and |, interpolation. Table 5 Comparison.

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Hadoop Paradigm for Satellite Environmental Big Data Processing

by Badr-Eddine Boudriki Semlali and

2019, International Journal of Agricultural and Environmental Information Systems

The important growth of industrial, transport and agriculture activities, has not led only to the air quality and climate changes issues, but also to the increase of the potential natural disasters. The emission of harmful gases,... more

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Towards Remote Sensing Datasets Collection and Processing

by Badr-Eddine Boudriki Semlali

2019, International Journal of Embedded and Real-Time Communication Systems

The world is witnessing important increases in industrial, transport and agriculture activities. This leads to economic growth, but, on the other hand, causes substantial damage in urban air, due to emissions of harmful gases, mainly CO,... more

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Chapter1

by Badr-Eddine Boudriki Semlali

2019, Towards Remote Sensing Datasets Collection and Processing

The world is witnessing important increases in industrial, transport and agriculture activities. This leads to economic growth, but, on the other hand, causes substantial damage in urban air, due to emissions of harmful gases, mainly CO,... more

Fig. 6. MDEO data formats
Fig. 7. Number of plots

Table 2. Thermals power plants of Morocco

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Remote Sensing: Aspects and Specifications within a Proposed Big Data Architecture

by Badr-Eddine Boudriki Semlali

2019, Remote Sensing: Aspects and Specifications within a Proposed Big Data Architecture

The important growth of industrial, transport and agriculture activities in Morocco , has lead to many air quality and climate changes issues, due to the emission of harmful gases , particularly: CO, SO2, NO2, and so on. we have used... more

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Development of a Near Real-time Air Pollution Map of Morocco

by Badr-Eddine Boudriki Semlali and

2019, Development of a Near Real-time Air Pollution Map of Morocco

Currently, the world is witnessing important increases of industrial, transport and agriculture activities. This leads to environmental changes and issues of air pollution, due to emission of harmful gases such as CO, SO2 and NO2.... more

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PLA(id): a tool for organising and sharing on-line building product information

by Salih Ofluoğlu

2018, Automation in Construction

This paper outlines the objectives and issues of a research project about on-line product information used by architects, engineers and other design professionals. After identifying some key issues pertinent to Web-based product... more

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Real-time access to orbital optical sensors for disaster early warning: A NATO science for peace sponsored partnership of universities in Morocco, Turkey and the USA

by Joseph E Quansah

2016

Enhancing the capacity of nations with respect to the early warning of disasters and the management of the sequellae of catastrophic events are essential components to regional sustainable development. The requisite infrastructure and... more

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Presentacion Cementeras y constructoras

by Neal Caffrey

2014

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มลพิษทางอากาศ

by Thawanhathai Sirapajungled

2014

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Applying Web-Based Product Libraries

by Richard Coyne

2010, Automation in Construction