A system was used to detect injuries in plant leaves by combining machine learning and the principles of image processing. A small agricultural robot was implemented for fine spraying by identifying infected leaves using image processing technology with four different forward speeds (35, 46, 63 and 80 cm/s). The results revealed that increasing the speed of the agricultural robot led to a decrease in the mount of supplements spraying and a detection percentage of infected plants. They also revealed a decrease in the percentage of supplements spraying by 46.89, 52.94, 63.07 and 76% with different forward speeds compared to the traditional method.
This research explores the obstacles teachers encounter in executing the smart schools initiative within the framework of Iraq, where educational facilities and digital preparedness are still at an early stage. Although worldwide trends reveal the growing use of smart technologies in education, Iraq has been hindered by systemic barriers, such as archaic curricula, restricted access to technologies, and an unqualified teaching staff. Data were collected using a validated questionnaire on 122 public school teachers working in Baghdad with a descriptive-analytical methodology. The study divided challenges into five areas: infrastructure, teacher preparedness, administrative support, curricular adaptation and cultural resistanc
... Show MoreBackground: Corn Syrup is food syrup higher of carbohydrate, depending on grade. The study aimed to assess efficiency of Corn syrup as cytological fixative.
Subjects and methods: This was laboratory based study, it has been conducted at Elrazi University included apparently 30 healthy students have been involved in this study.
Results: Out of 30 smears fixed with 95% alcohol, 76.7% (n=23) shows excellent nuclear stain, 23.3% (n= 7) shows good nuclear stain. 70% (n=21) show excellent cytoplasmic stain, 26.7% (n=8) shows good cytoplasmic stain, 3.3% (n=1) shows poor cytoplasmuc stain.
Out of 30 smears fixed with corn solution, 60
... Show MoreThis deals with estimation of Reliability function and one shape parameter (?) of two- parameters Burr – XII , when ?(shape parameter is known) (?=0.5,1,1.5) and also the initial values of (?=1), while different sample shze n= 10, 20, 30, 50) bare used. The results depend on empirical study through simulation experiments are applied to compare the four methods of estimation, as well as computing the reliability function . The results of Mean square error indicates that Jacknif estimator is better than other three estimators , for all sample size and parameter values
The experiment was carried out in the Department of Biology, College of Education for Pure Science –Ibn AL Haitham, University of Baghdad, Iraq, during the growing season 2017 – 2018. The objective was to find out the effect of foliar spraying of tryptophan and IQ COMBI nano fertilizer on cumin plants. The obtained results show that both tryptophan and IQ COMBI nano fertilizer increased plant height, root length, shoot dry weight, the content of nitrogen, phosphorus, potassium, protein percentage, no. compound umbel.plant-1, wt. seeds. plant-1. The optimum treatment combination was calculated as 30 mg.L-1 tryptophan, 1000mg.L-1 IQ COMBI nano fertilizer, which gave the highest values for most of the parameters studied
This investigation proposed an identification system of offline signature by utilizing rotation compensation depending on the features that were saved in the database. The proposed system contains five principle stages, they are: (1) data acquisition, (2) signature data file loading, (3) signature preprocessing, (4) feature extraction, and (5) feature matching. The feature extraction includes determination of the center point coordinates, and the angle for rotation compensation (θ), implementation of rotation compensation, determination of discriminating features and statistical condition. During this work seven essential collections of features are utilized to acquire the characteristics: (i) density (D), (ii) average (A), (iii) s
... Show MoreThis study explores the challenges in Artificial Intelligence (AI) systems in generating image captions, a task that requires effective integration of computer vision and natural language processing techniques. A comparative analysis between traditional approaches such as retrieval- based methods and linguistic templates) and modern approaches based on deep learning such as encoder-decoder models, attention mechanisms, and transformers). Theoretical results show that modern models perform better for the accuracy and the ability to generate more complex descriptions, while traditional methods outperform speed and simplicity. The paper proposes a hybrid framework that combines the advantages of both approaches, where conventional methods prod
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