The agriculture around the world faced many difficulties and the important was to reduce inputs of chemical fertilizers and pesticides and increase the total yield specially with the continuous grow of populations numbers at the world expected to reach more than 9 billion by 2050. In other hand there are other problems which make the challenges bigger such as wars, biotic and abiotic stress, and diseases. The scientists tried to find solutions by using Nano-fertilization which consider a modern way to quickly grow up the yield and decrease use the chemicals. The use of nanotechnology may be destructive on human and the environment due to fast accumulation in the tissues of alive bodies which obligate the researchers to find the correct method and doses of Nano fertilizers for the different plants beside the attempt to use fertilizer environment friendly with high efficiency on growth and yield. Many products of nanotechnology were used in agriculture as fertilizers, pesticides, and water purification and while these products use expand, we need to make our steps fast to be careful of the advantages use which may appears in the future on human health and his environments. In Iraq there is many of challenges faced plant production such as wars, migrations, pollutions, and salinity so a lot of farmers found that Nano-fertilizers are a good technique to reduce their loss while there are many studies cautioned of bad use of nanomaterials which its dangerous is bigger than chemicals due its ability to permeability and accumulations.
Lattakia city faces many problems related to the mismanagement of solid waste, as the disposal process is limited to the random Al-Bassa landfill without treatment. Therefore, solid waste management poses a special challenge to decision-makers by choosing the appropriate tool that supports strategic decisions in choosing municipal solid waste treatment methods and evaluating their management systems. As the human is primarily responsible for the formation of waste, this study aims to measure the degree of environmental awareness in the Lattakia Governorate from the point of view of the research sample members and to discuss the effect of the studied variables (place of residence, educational level, gender, age, and professional status) o
... Show MoreMachine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To
... Show MoreA hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m
... Show MoreFace recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security
... Show MoreThis research aims to identify the effectiveness of counseling by using the technique of self-talkin developing the habits of mind among middle school students by testing important hypotheses, and choosing the experimental design for the two groups (experimental - control). The classification of "Costa & Kallick" was adopted to measure the habits of the mind, and the scale consisted of (64) items, and after confirming the psychometric properties of the scale, the researcher applied it to the research sample (487) students from middle school students. One of the students who got the lowest marks after answering the scale. purpose of applying the experiment. He divided them into two groups, one of them is experimental (10) students, as
... Show MoreThis study was conducted at the College of Education for Pure Sciences (Ibn Al-Haitham), University of Baghdad. The aim of this study was to isolate and diagnose fungi from fish feedstuff samples, and also detection of aflatoxin B1 and ochratoxin A in fish muscles and feedstuffs. Randomly, the samples were collected from some fish farms from Baghdad, Babil, Wasit, Anbar, and Salah al-Din provinces. This study included the collection of 35 feedstuff samples and 70 fish muscle samples, and each of the two fish samples fed on one sample of the feedstuff. The results showed the presence of several genera of different fungi including Aspergillus spp, Mucor spp., Penicillium spp., Yeast spp., Fusarium spp., Rhizopus spp., Scopiolariopsis spp., Ep
... Show MoreDevelopment of improved methods for the synthesis of metal oxide nanoparticles are of high priority for the advancement of material science and technology. Herein, the biosynthesis of ZnO using hydrahelix of beta vulgaris and the seed of abrus precatorius as an aqueaus extracts adduced respectivily as stablizer and reductant reagent. The support are characterized by spectroscopic methods ( Ft-IR, Uv-vis ).The FTIR confirmed the presence of ZnO band. The Uv-visible showed absorption peak at corresponds to the ZnO nanostructures. X-ray diffraction, scaning electron microscopy (SEM), dispersive X-ray spectroscopy (EDX) techniques are taken to investigation the size, structure and composition of synthesised ZnO nanocrystals. The XRD pattern mat
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