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.
In the present work, different remote sensing techniques have been used to analyze remote sensing data spectrally using ENVI software. The majority of algorithms used in the Spectral Processing can be organized as target detection, change detection and classification. In this paper several methods of target detection have been studied such as matched filter and constrained energy minimization.
The water body mapping have been obtained and the results showed changes on the study area through the period 1995-2000. Also the results that obtained from applying constrained energy minimization were more accurate than other method comparing with the real situation.
In this paper, integrated quantum neural network (QNN), which is a class of feedforward
neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that
... Show MoreData compression offers an attractive approach to reducing communication costs using available bandwidth effectively. It makes sense to pursue research on developing algorithms that can most effectively use available network. It is also important to consider the security aspect of the data being transmitted is vulnerable to attacks. The basic aim of this work is to develop a module for combining the operation of compression and encryption on the same set of data to perform these two operations simultaneously. This is achieved through embedding encryption into compression algorithms since both cryptographic ciphers and entropy coders bear certain resemblance in the sense of secrecy. First in the secure compression module, the given text is p
... Show MoreBlockchain technology relies on cryptographic techniques that provide various advantages, such as trustworthiness, collaboration, organization, identification, integrity, and transparency. Meanwhile, data analytics refers to the process of utilizing techniques to analyze big data and comprehend the relationships between data points to draw meaningful conclusions. The field of data analytics in Blockchain is relatively new, and few studies have been conducted to examine the challenges involved in Blockchain data analytics. This article presents a systematic analysis of how data analytics affects Blockchain performance, with the aim of investigating the current state of Blockchain-based data analytics techniques in research fields and
... Show MoreIn this study, the mobile phone traces concern an ephemeral event which represents important densities of people. This research aims to study city pulse and human mobility evolution that would be arise during specific event (Armada festival), by modelling and simulating human mobility of the observed region, depending on CDRs (Call Detail Records) data. The most pivot questions of this research are: Why human mobility studied? What are the human life patterns in the observed region inside Rouen city during Armada festival? How life patterns and individuals' mobility could be extracted for this region from mobile DB (CDRs)? The radius of gyration parameter has been applied to elaborate human life patterns with regards to (work, off) days for
... Show MoreEven though image retrieval is considered as one of the most important research areas in the last two decades, there is still room for improvement since it is still not satisfying for many users. Two of the major problems which need to be improved are the accuracy and the speed of the image retrieval system, in order to achieve user satisfaction and also to make the image retrieval system suitable for all platforms. In this work, the proposed retrieval system uses features with spatial information to analyze the visual content of the image. Then, the feature extraction process is followed by applying the fuzzy c-means (FCM) clustering algorithm to reduce the search space and speed up the retrieval process. The experimental results show t
... Show MoreIn this study, we review the ARIMA (p, d, q), the EWMA and the DLM (dynamic linear moodelling) procedures in brief in order to accomdate the ac(autocorrelation) structure of data .We consider the recursive estimation and prediction algorithms based on Bayes and KF (Kalman filtering) techniques for correlated observations.We investigate the effect on the MSE of these procedures and compare them using generated data.
A loS.sless (reversible) data hiding (embedding) method inside an image (translating medium) - presented in the present work using L_SB (least significant bit). technique which enables us to translate data using an image (host image), using a secret key, to be undetectable without losing any data or without changing the size and the external scene (visible properties) of the image, the hid-ing data is then can be extracted (without losing) by reversing &n
... Show MoreData hiding is the process of encoding extra information in an image by making small modification to its pixels. To be practical, the hidden data must be perceptually invisible yet robust to common signal processing operations. This paper introduces a scheme for hiding a signature image that could be as much as 25% of the host image data and hence could be used both in digital watermarking as well as image/data hiding. The proposed algorithm uses orthogonal discrete wavelet transforms with two zero moments and with improved time localization called discrete slantlet transform for both host and signature image. A scaling factor ? in frequency domain control the quality of the watermarked images. Experimental results of signature image
... Show MoreThe research aims to show the effect of some short-term debt instruments (central treasury transfers, cash credit granted to the government by commercial banks) on the production of the wheat crop in Iraq, through its effect on money supply during the period (1990-2018), As the study includes two models according to the statistical program (Eviews9), the first model included measuring the effect of short-term debt instruments on money supply, and the second measuring the extent of the money supply's impact on Wheat crop production, as the results of the standard analysis showed that the short-term debt instruments used in the model were Significant effect on wheat crop production indirectly through its effect on money supply, As
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