Carbon monoxide (CO) plays an important indirect greenhouse gases due to its influences on the budgets of hydroxyl radicals (OH) and Ozone (O3). The atmospheric carbon monoxide (CO) observations can only be made on global and continental scales by remote sensing instruments situated in space. One of instrument is the Measurements of Pollution in the Troposphere (MOPITT), which is designed to measure troposphere CO and CH4 by use of a nadir-viewing geometry and was launched aboard the Earth Observing System (EOS) Terra spacecraft on 18 December 1999. Results from the analysis of the retrieved monthly (1ºх1º) spatial grid resolution, from the MOPITT data were utilized to analyze the distribution of CO surface mixing ratio in Iraq for the year 2010. The analysis shows the seasonal variations in the CO surface fluctuate considerably observed between winter and summer. The mean and the standard deviation of monthly CO was (172.076 ± 62.026 ppbv) for the entire study period. The CO value in winter was higher than its values in summer season and its values over Industrial and congested urban zones higher than its values in the rest of regions throughout the year. Maximum values occurred in the northern region (234.105 ppbv) on February at Erbil, were attributed to the increased human activity, geographic nature of the areas and climatic variations. The elevation of CO values on the south-eastern region during the June - November period was due to the emissions from the oil extraction and the burning of agricultural residues in the paddy fields. A greater draws down of the CO occurs over pristine desert environment in the western region (110.047 ppbv) on July at Al Anbar (41.5°log. × 32.5°lat.). The monthly CO surface VMR maps for 2010 were generated using kriging algorithm technique. The MOPITT data and the Satellite measurements are able to measure the increase of the atmosphere CO concentrations over different regions.
Cadastral map environment is directed, more than ever before, towards Artificial Intelligence use to produce fast and accurate maps and keep up with the huge population growth. The traditional approach currently in production of maps is expensive and effort-intensive in addition to be considered as highly time-consuming process. UAV-based cadastral mapping imagery that use automatic techniques are newly being exploited to accelerate the process of production or updating. The state-of-the-art intelligent algorithms are capable to extract land boundaries from images better than conventional techniques. This paper presents an automatic workflow of cadastral map production based on land boundary and automatic f
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In this paper a new idea was introduced which is finding a new distribution from other distributions using mixing parameters; wi where 0 < wi < 1 and . Therefore we can get many mixture distributions with a number of parameters. In this paper I introduced the idea of a mixture Weibull distribution which is produced from mixing two Weibull distributions; the first with two parameters, the scale parameter , and the shape parameter, and the second also has the scale parameter , and the shape parameter, in addition to the location parameter, . These two distributions were mixed using a new parameter which is the mixing parameter w which represents the proportion
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Secure information transmission over the internet is becoming an important requirement in data communication. These days, authenticity, secrecy, and confidentiality are the most important concerns in securing data communication. For that reason, information hiding methods are used, such as Cryptography, Steganography and Watermarking methods, to secure data transmission, where cryptography method is used to encrypt the information in an unreadable form. At the same time, steganography covers the information within images, audio or video. Finally, watermarking is used to protect information from intruders. This paper proposed a new cryptography method by using thre
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Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on
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