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.
Water quality planning relies on Biochemical Oxygen Demand BOD. BOD testing takes five days. The Particle Swarm Optimization (PSO) is increasingly used for water resource forecasting. This work designed a PSO technique for estimating everyday BOD at Al-Rustumiya wastewater treatment facility inlet. Al-Rustumiya wastewater treatment plant provided 702 plant-scale data sets during 2012-2022. The PSO model uses the daily data of the water quality parameters, including chemical oxygen demand (COD), chloride (Cl-), suspended solid (SS), total dissolved solids (TDS), and pH, to determine how each variable affects the daily incoming BOD. PSO and multiple linear regression (MLR) findings are compared, and their performance is evaluated usin
... Show MoreWater quality planning relies on Biochemical Oxygen Demand BOD. BOD testing takes five days. The Particle Swarm Optimization (PSO) is increasingly used for water resource forecasting. This work designed a PSO technique for estimating everyday BOD at Al-Rustumiya wastewater treatment facility inlet. Al-Rustumiya wastewater treatment plant provided 702 plant-scale data sets during 2012-2022. The PSO model uses the daily data of the water quality parameters, including chemical oxygen demand (COD), chloride (Cl-), suspended solid (SS), total dissolved solids (TDS), and pH, to determine how each variable affects the daily incoming BOD. PSO and multiple linear regression (MLR) findings are compared, and their perfor
... Show MoreThis research examines the scientific impact of Al-Hafiz Sharaf al-Din al-Damiati, who descended from a famous scholarly family known as (Al-Damiati) in reference to the city of Damietta in Egypt. This family was distinguished by producing scholars and writers during the Ayyubid and Mamluk eras, the most prominent of whom was Sharaf al-Din. He was preceded by a scholar of no lesser scientific stature, Shams al-Din al-Damiati (d. 693 AH), who was famous for his knowledge of the science of readings. Sharaf al-Din al-Damiati was famous for his mastery of the science of hadith and genealogy. The political situation that prevailed during his era was represented by the occupation of the city of Baghdad in 656 AH/1258 AD, the end of the Abbasid Ca
... Show MoreDiabetes imposes a substantial public health burden; according to the International Diabetes Federation, there were about 3.4 million diabetes related deaths worldwide in 2024, and in Iraq, the Federation reports that one in nine adults lives with diabetes in 2024, with 14,683 adult deaths attributable to diabetes and a total diabetes related health expenditure of 2,078 million United States dollars. The dataset analyzed in this study contains 1,000 records collected in 2020 from two Iraqi teaching hospitals and includes multiple clinical and laboratory measurements with three outcome classes, namely Non diabetic, Pre diabetic, and Diabetic, with a low prevalence of the Pre diabetic class and an imbalanced overall class distribution; the da
... Show MoreTraffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c
... Show MoreIn this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database
Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to
... Show MoreIn The Name of Allah Most Gracious Most Merciful
Scholars, past and present, have paid attention to the books of Fasting and Hajj, and they have compiled literature on that, and they have written treatises and researches. The best days, and as for the pilgrimage, it is one of the great pillars of Islam, which God Almighty has distinguished by making its rituals in the best of places, which is the Sacred House of God.