Accurate land use and land cover (LU/LC) classification is essential for various geospatial applications. This research applied a Spectral Angle Mapper (SAM) classifier on the Landsat 7 (ETM+ 2010) & 8 (OLI 2020) satellite scenes to identify the land cover materials of the Shatt al-Arab region which is located in the east of Basra province during ten years with an estimate of the spectral signature using ENVI 5.6 software of each cover with the proportion of its area to the area of the study region and produce maps of the classified region. The bands of these datasets were analyzed using the Optimum Index Factor (OIF) statistic. The highest OIF represents the best and most appropriate band combination calculated for the classification process are (SWIR_2, SWIR_1, Blue) and (SWIR_2, SWIR_1, coastal aerosol) bands combination at (100.236 & 104.154) for ETM+, and OLI datasets, respectively, which adopted to obtain the most accurate interpretation of the land cover. The Landsat 7 (ETM+ 2010) is selected as a reference year to study the change in land cover features through ten years for this region using the novel Scene Optimum Index Factor (SOIF), which was suggested in this research. The amount of change for vegetation cover was 34 %, using the SAM classifier. The urban class was the most stable, and the rate of change was 23 %. The most affected were the water bodies, where the rate of change reached 73% due to the region falling into the tails of rivers, as well as the lack of water discharges coming from neighbouring and upstream countries. The research provides important information about land cover changes over the past decade due to the precise spectral analyses, showing the need for monitoring natural resources, especially in environmentally sensitive areas such as water bodies and vegetation cover. Environmental conservation efforts and continuous planning in affected regions may be supported by these findings.
With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect
... Show MoreAssessing the accuracy of classification algorithms is paramount as it provides insights into reliability and effectiveness in solving real-world problems. Accuracy examination is essential in any remote sensing-based classification practice, given that classification maps consistently include misclassified pixels and classification misconceptions. In this study, two imaginary satellites for Duhok province, Iraq, were captured at regular intervals, and the photos were analyzed using spatial analysis tools to provide supervised classifications. Some processes were conducted to enhance the categorization, like smoothing. The classification results indicate that Duhok province is divided into four classes: vegetation cover, buildings,
... Show MoreTreated effluent wastewater is considered an alternative water resource which can provide an important contribution for using it in different purposes, so, the wastewater quality is very important for knowing its suitability for different uses before discharging it into fresh water ecosystems. The wastewater quality index (WWQI) may be considered as a useful and effective tool to assess wastewater quality by indicating one value representing the overall characteristic of the wastewater. It could be used to indicate the suitability of wastewater for different uses in water quality management and decision making. The present study was conducted to evaluate the Al-Diwaniyah sewage treatment plant (STP) effluent quality based on wastewa
... Show MoreThe purpose of this study was to measure serum levels of insulin-like growth factor-binding protein (IGFBP7), Insulin-like Growth Factor 1 (IGF-1), Growth Hormone (GH), Interleukin 6 (IL-6) and insulin in acromegaly patients and healthy controls. The acromegaly group had 60 patients, while the population group had 30 people who had never had acromegaly before. The concentration of IGFBP7, IGF-1, GH, IL-6, and insulin were determined. The results of the present study indicate that IGFBP7 level in the acromegaly group was significantly lower (1.690.07 ng/mL vs. 2.740.12 ng/mL, respectively, p = 0.001). IGF-1, GH, IL-6, and insulin concentrations were also significantly higher in acromegaly patients. The diagnostic accuracy (2.194) was exce
... Show MoreRandom matrix theory is used to study the chaotic properties in nuclear energy spectrum of the 24Mg nucleus. The excitation energies (which are the main object of this study) are obtained via performing shell model calculations using the OXBASH computer code together with an effective interaction of Wildenthal (W) in the isospin formalism. The 24Mg nucleus is assumed to have an inert 16O core with 8 nucleons (4protons and 4neutrons) move in the 1d5/2, 2s1/2 and 1d3/2 orbitals. The spectral fluctuations are studied by two statistical measures: the nearest neighb
Objective : Multiple sclerosis (MS) is a common neurological disease deeply linked with the immune-inflammatory disorders whereas the term (multiple) mostly refers to the multi-focal zones of Inflammation caused by lymphocytes and macrophages infiltration besides oligodendrocytes death. Accordingly , the dysfunctional immune system able to damage myelin ( a pivotal component of the central nervous system ) which responsible for communication among neurons. The aim of the present study is to innovate a biochemical relationship between MS and thyroid hormones (THs) by highlighting immunological responses and also to examine the action of Interferon beta (IFNβ) drug on thyroid hormone (THs) and thyroid stimulation hormone (TSH). Materials and
... Show MoreThis study aims to determine the reasons for the increase in the frequency of sand and dust storms in the Middle East and to identify their sources and mitigate them. A set of climatic data from 60 years (1960–2022) was analyzed. Sand storms in Iraq are a silty sand mature arkose composed of 72.7% sand, 25.1% silt, and 2.19% clay; the clay fraction in dust storms constitutes 70%, with a small amount of silt (20.6%) and sand (9.4%). Dust and sand storms (%) are composed of quartz (49.2, 67.1), feldspar (4.9, 20.9), calcite (38, 5), gypsum (4.8, 0.4), dolomite (0.8, 1.0), and heavy minerals (3.2, 6.6). Increasing temperatures in Iraq, by an average of 2 °C for sixty years, have contributed to an increase in the number of dust storm
... Show MoreAbstract Objectives: Malocclusion was and remains one of the most common problems which affects the psyche and social status of the individual, so the estimation of the malocclusion severity and needs a percentage of orthodontic treatment of Iraqi patients is the aim of this study. Method: A randomly selected 150 pairs of study models (48 male and 102 female) were involved in this study for patients attending an orthodontic clinic at College of Dentistry/ University of Baghdad seeking for treatment. The DAI scores were collected according to WHO guidelines directly from the study model with a digital caliper, score was calculated using the regression equation of 10 occlusal traits. The dental casts were classified into four groups to determ
... Show MoreIn this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respe
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