Spot panchromatic satellite image had been employed to study and know the difference Between ground and satellite data( DN ,its values varies from 0-255) where it is necessary to convert these DN values to absolute radiance values through special equations ,later it converted to spectral reflectance values .In this study a monitoring of the environmental effect resulted from throwing the sewage drainages pollutants (industrial and home) into the Tigris river water in Mosul, was achieved, which have an effect mostly on physical characters specially color and turbidity which lead to the variation in Spectral Reflectance of the river water ,and it could be detected by using many remote sensing techniques. The contaminated areas within the water of the river which represents the difference in the reflectance values were isolated and signed, as well as the field estimations, which had been done by using spectrometer device, which gave an acceptable agreement with satellite data considering time difference between these estimations. satellite imagery analysis program ERDAS version 8.4 was used to determine the values of Spectral Reflectance in the satellite image. A geographic information systems through the ARC INFO has been used to draw photo map of the study area determined it specific sites of measuring the Reflectance, which represent areas that are near the sources of pollution and the other various regions along the river.
This study was conducted for the purpose of exploring the relationship between positive thinking and academic achievement in art history. And it relates to the student’s personality, intelligence, abilities and economic and social level. The sample of the study consisted of (40) male and female students from the first stage students - Department of Art Education in the Faculty of Fine Arts / Morning Study, A positive thinking questionnaire was applied to them, and the study found that there is no positive relationship between positive thinking and academic achievement in art history.
The power generation of solar photovoltaic (PV) technology is being implemented in every nation worldwide due to its environmentally clean characteristics. Therefore, PV technology is significantly growing in the present applications and usage of PV power systems. Despite the strength of the PV arrays in power systems, the arrays remain susceptible to certain faults. An effective supply requires economic returns, the security of the equipment and humans, precise fault identification, diagnosis, and interruption tools. Meanwhile, the faults in unidentified arc lead to serious fire hazards to commercial, residential, and utility-scale PV systems. To ensure secure and dependable distribution of electricity, the detection of such ha
... Show MoreImage quality plays a vital role in improving and assessing image compression performance. Image compression represents big image data to a new image with a smaller size suitable for storage and transmission. This paper aims to evaluate the implementation of the hybrid techniques-based tensor product mixed transform. Compression and quality metrics such as compression-ratio (CR), rate-distortion (RD), peak signal-to-noise ratio (PSNR), and Structural Content (SC) are utilized for evaluating the hybrid techniques. Then, a comparison between techniques is achieved according to these metrics to estimate the best technique. The main contribution is to improve the hybrid techniques. The proposed hybrid techniques are consisting of discrete wavel
... Show MoreWith 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 MoreThe aim of this paper is to construct cyclic subgroups of the projective general linear group over from the companion matrix, and then form caps of various degrees in . Geometric properties of these caps as secant distributions and index distributions are given and determined if they are complete. Also, partitioned of into disjoint lines is discussed.
Soil pH is one of the main factors to consider before undertaking any agricultural operation. Methods for measuring soil pH vary, but all traditional methods require time, effort, and expertise. This study aimed to determine, predict, and map the spatial distribution of soil pH based on data taken from 50 sites using the Kriging geostatistical tool in ArcGIS as a first step. In the second step, the Support Vector Machines (SVM) machine learning algorithm was used to predict the soil pH based on the CIE-L*a*b values taken from the optical fiber sensor. The standard deviation of the soil pH values was 0.42, which indicates a more reliable measurement and the data distribution is normal.
Geomechanical modelling and simulation are introduced to accurately determine the combined effects of hydrocarbon production and changes in rock properties due to geomechanical effects. The reservoir geomechanical model is concerned with stress-related issues and rock failure in compression, shear, and tension induced by reservoir pore pressure changes due to reservoir depletion. In this paper, a rock mechanical model is constructed in geomechanical mode, and reservoir geomechanics simulations are run for a carbonate gas reservoir. The study begins with assessment of the data, construction of 1D rock mechanical models along the well trajectory, the generation of a 3D mechanical earth model, and runni
The application of the test case prioritization method is a key part of system testing intended to think it through and sort out the issues early in the development stage. Traditional prioritization techniques frequently fail to take into account the complexities of big-scale test suites, growing systems and time constraints, therefore cannot fully fix this problem. The proposed study here will deal with a meta-heuristic hybrid method that focuses on addressing the challenges of the modern time. The strategy utilizes genetic algorithms alongside a black hole as a means to create a smooth tradeoff between exploring numerous possibilities and exploiting the best one. The proposed hybrid algorithm of genetic black hole (HGBH) uses the
... Show MoreECG is an important tool for the primary diagnosis of heart diseases, which shows the electrophysiology of the heart. In our method, a single maternal abdominal ECG signal is taken as an input signal and the maternal P-QRS-T complexes of original signal is averaged and repeated and taken as a reference signal. LMS and RLS adaptive filters algorithms are applied. The results showed that the fetal ECGs have been successfully detected. The accuracy of Daisy database was up to 84% of LMS and 88% of RLS while PhysioNet was up to 98% and 96% for LMS and RLS respectively.