Sustainable plant protection and the economy of plant crops worldwide depend heavily on the health of agriculture. In the modern world, one of the main factors influencing economic growth is the quality of agricultural produce. The need for future crop protection and production is growing as disease-affected plants have caused considerable agricultural losses in several crop categories. The crop yield must be increased while preserving food quality and security and having the most negligible negative environmental impact. To overcome these obstacles, early discovery of satisfactory plants is critical. The use of Advances in Intelligent Systems and information computer science effectively helps find more efficient and low-cost solutions. This paper proposed a multiclass classification model that aims to detect diseases in three types of fruit using the leaves plant images dataset. These three types of fruit are (Apple, Cherry, and Strawberry) where Apples have three disease dataset categories (Apple Scab, Black Rot, and Cedar Rust) as well as healthy apple dataset, Cherry have Powdery Mildew disease dataset category and healthy dataset, and Strawberry have leaf Scorch disease dataset category and healthy dataset. These datasets are based on the Kaggle website. These multiclass classifications need several steps of processing; the first step is preprocessing the dataset by resizing all images to the same size, segmentation, and removing noise; then, feature extraction from color and texture features; the next step is feature selection to find optimal features by using the Salp Swarm algorithm (SSA); and classification by using machine learning models (Random Forest), (CatBoost), and (XGBoost). In the final step, evaluation of the performance was used to select several matrices: Accuracy, precision, recall, and F1-score.
Most vegetation’s are Land cover (LC) for the globe, and there is an increased attention to plants since they represent an element of balance to natural ecology and maintain the natural balance of rapid changes due to systematic and random human uses, including the subject of the current study (Bassia eriophora ) Which represent an essential part of the United Nations system for land cover classification (LCCS), developed by the World Food Organization (FAO) and the world Organization for environmental program (UNEP), to observe basic environmental elements with modern techniques. Although this plant is distributed all over Iraq, we found that this plant exists primarily in the middle
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The current study included the isolation, purification and cultivation of blue-green alga Oscillatoria pseudogeminata G.Schmidle from soil using the BG-11liquid culture medium for 60 days of cultivation. The growth constant (k) and generation time (G) were measured which (K=0.144) and (G=2.09 days).
Microcystins were purified and determined qualitatively and quantitatively from this alga by using the technique of enzyme linked immunosorbent assay (Elisa Kits). The alga showed the ability to produce microcystins in concentration reached 1.47 µg/L for each 50 mg DW. Tomato plants (Lycopersicon esculentum) aged two months were irrigated with three concentrations of purified microcystins 0.5 , 3.0 and 6.0
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Background Parkinson’s disease (PD) is a common neurodegenerative disease that is linked to several motor and nonmotor symptoms, including sleep disturbances. Patient quality of life has been shown to be disproportionally impacted by disease. Objectives To investigate sleep quality among individuals with PD, and to assess the severity of sleep disturbances and their impact on daytime activities. Subjects and methods A case‒control with 44 patients with Parkinson’s disease and 80 apparently healthy control participants was recruited from several hospitals and clinics. Each participant provided a thorough medical history and underwent a physical examination, and a questionnaire comprising the standard PSQI was used to assess sleep qua
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There are many methods of searching large amount of data to find one particular piece of information. Such as find name of person in record of mobile. Certain methods of organizing data make the search process more efficient the objective of these methods is to find the element with least cost (least time). Binary search algorithm is faster than sequential and other commonly used search algorithms. This research develops binary search algorithm by using new structure called Triple, structure in this structure data are represented as triple. It consists of three locations (1-Top, 2-Left, and 3-Right) Binary search algorithm divide the search interval in half, this process makes the maximum number of comparisons (Average case com
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The experiment was conducted in the old botanical garden belong to Biology Department/ College of Education for Pure Science - Ibn Al-Haitham/Baghdad University for growing season 2015-2016 to study the effect of irrigation with four concentrations of sodium chloride (0, 50, 100, 150) mM.L-1 and spraying with selenium in three concentrations (0, 10, 20) mgL-1 on growth of broad bean plant using clay pots. The experiment was design according to completely randomized design (CRD) with three replications. Results indicated that broad bean plant irrigated with saline water and increasing concentrations of sodium chloride in growth medium caused a significant decreased in the plant growth parameters (plant height, no. of compound leaves. Plant-1
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The river water salinity is a major concern in many countries, and salinity can be expressed as total dissolved solids. So, the water salinity impact of the river is one of the major factors effects of water quality. Tigris river water salinity increase with streamline and time due to the decrease in the river flow and dam construction from neighboring countries. The major objective of this research to developed salinity model to study the change of salinity and its impact on the Al-Karkh, Sharq Dijla, Al-Karama, Al-Wathba, Al-Dora, and Al-Wihda water treatment plant along Tigris River in Baghdad city using artificial neural network model (ANN). The parameter used in a model built is (Turbidity, Ec, T.s, S.s, and TDS in)
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A substantial percentage of the world’s energy consumption (almost 40%) and carbon dioxide (CO2) emissions (around 37%) come from the construction industry, especially schools. This work presents a new hybrid artificial intelligence (AI) engineering model that aims to maximize energy performance on campuses in a holistic way. Modules for data-driven forecasting, metaheuristic optimization, and real-time adaptive control are all part of the concept. A thorough energy simulation of a university campus building is used in conjunction with the AI model to assess its performance through a co-simulation framework. Findings show that yearly peak electricity demand may be reduced by 18.7% and total site energy consumption by 22.4% when co
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l development in addition to environmental reform, which is not possible at its best, and from this the faculties of physical education and sports science realize the scale of the problem and its importance in the development of society that this all puts on the faculties of education Physical and sports sciences are a very difficult task and an end in holiness, for it is the responsibility of the human development service and its leadership, because the community leaders and its elites are those who value their direction and future more than others. The importance of this study comes from the goal of sustainable development to maximizing pain. The net gain from higher education while ensuring the preservation of the quality of reso
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