The detection of diseases affecting plant is very important as it relates to the issue of food security, which is a very serious threat to human life. The system of diagnosis of diseases involves a series of steps starting with the acquisition of images through the pre-processing, segmentation and then features extraction that is our subject finally the process of classification. Features extraction is a very important process in any diagnostic system where we can compare this stage to the spine in this type of system. It is known that the reason behind this great importance of this stage is that the process of extracting features greatly affects the work and accuracy of classification. Proper selection of the right features leads to high accuracy in the system diagnostics and vice versa. The proposed system collect images of different crop (Rice, cotton and tomato) disease, we will enter the images of cropping them , then Re-size the images to fixed size, then improve the image through Fuzzy histogram equalization (FHE) , then perform image segmentation using color based K-means and finally compare the methods of features extraction (Percentage of Leaf Area Infected (PI),Texture-Based Features, Color Moments, Features obtained by Color Co-occurrence Method and Shape based Features) we found that the use of 4 methods together (Percentage of Leaf Area Infected (PI),Texture-Based Features, Color Moments and Shape based Features) produce excellent result..
Audio classification is the process to classify different audio types according to contents. It is implemented in a large variety of real world problems, all classification applications allowed the target subjects to be viewed as a specific type of audio and hence, there is a variety in the audio types and every type has to be treatedcarefully according to its significant properties.Feature extraction is an important process for audio classification. This workintroduces several sets of features according to the type, two types of audio (datasets) were studied. Two different features sets are proposed: (i) firstorder gradient feature vector, and (ii) Local roughness feature vector, the experimentsshowed that the results are competitive to
... Show MoreStaphylococcus lugdunensis, isolation between 12.5 to 1.8% routine works may be a possible peroral route of infective endocarditis and found in the oral cavity by examined using saliva. Similar supragingival plaque isolation was observed. The increased bacteria resistance to antibiotics multiple have led to novel methods for resistance bacteria; antimicrobial agents are well known (ZnO NPs) by biological method and are lower toxicity and biology safety ZnNOPs activity by plant extraction and less toxicity as well as bio-safe. The nanoparticle was synthesized by biological method (Green) by barberry (Berberis vulgaris) extract. In this study using (WAD) method using different concentrations between (128, 64, 32, and 16) mg/mL of ZnO NPs, The
... Show MoreStaphylococcus lugdunensis, isolation between 12.5 to 1.8% routine works may be a possible peroral route of infective endocarditis and found in the oral cavity by examined using saliva. Similar supragingival plaque isolation was observed. The increased bacteria resistance to antibiotics multiple have led to novel methods for resistance bacteria; antimicrobial agents are well known (ZnO NPs) by biological method and are lower toxicity and biology safety ZnNOPs activity by plant extraction and less toxicity as well as bio-safe. The nanoparticle was synthesized by biological method (Green) by barberry (Berberis vulgaris) extract. In this study using (WAD) method using different concentrations between (128, 64, 32, and 16) mg/mL of ZnO
... Show MoreThe objective of the work was to study the changes in height and stem diameter of sunflower plants during growth stages under hardening conditions to drought tolerance. Field experiments were carried out during the spring season of 2000 and2001. Agricultural practices were made according to recommendations.Asplit-split plots design was used with three replications.The main plots included irrigation treatments:irrigation to100%(full irrigation),75and50%of available water.The sub plots were the cultivars Euroflor and Flame.The sub-sub plots represented four seed soaking treatments:Control(unsoaking), soaking in water ,Paclobutrazol solution(250ppm),and Pix solution(500ppm). The soaking continued for 24 hours then seeds were dried at room
... Show MoreIn order to study the effect of inoculation with mycorrhiza and fertilization with plant residues on the growth of plants, we used two factors: the first two levels of mycorrhiza inoculation, Glumus mossea (0 and 10 g.pot-1) and the second factor, four levels of plant residues (10 g.pot-1) celery plant residues, 10 g pot-1 mint residues, and 10 g pot-1 black bean seed residues. Mychorrizal treatment (10 g pot-1) increased the number of mycorrhiza spores and the infection percentage of mycorrhizal by 917.44% and 13088.23%, respectively; celery treatment (10 g.pot-1) increased the chlorophyll index in the leaves and height of the chard plant by 31.34% and 94.04%, respectively; and black seed treatment (10 g.pot-1) increased the percen
... Show MoreChaotic features of nuclear energy spectrum in 68Ge nucleus are investigated by nuclear shell model. The energies are calculated through doing shell model calculations employing the OXBASH computer code with effective interaction of F5PVH. The 68Ge nucleus is supposed to have an inert core of 56Ni with 12 nucleons (4 protons and 8 neutrons) move in the f5p-model space ( and ). The nuclear level density of considered classes of states is seen to have a Gaussian form, which is in accord with the prediction of other theoretical studies. The statistical fluctuations of the energy spectrum (the level spacing P(s) and the Dyson-Mehta (or statistics) are well described by the Gaussian orthogonal ens
... Show MoreCassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has
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