Automated detection of Dubas palm infestation by image processing techniques has practical significance as it can improve agricultural efficiency, increase crop yield and quality, protect the environment, and provide data-driven insights. It also reduces the human effort required for pest control and enhances sustainability. In this study, we aimed to automate the detection of Dubas bug infestation in palm trees using deep learning with transfer learning residual neural networks. Based on four models: InceptionResNetV2, ResNet18, ResNet50, and ResNet101, the data used in this study were obtained by drone photography, many images were taken, and then the infected area was extracted. Using two types of data, 185 infected images and 185 healthy images were extracted. Through analyzing the results, we reached a conclusion regarding the automated detection of Dubas bug infestations. In palm trees, ResNet18 and ResNet50 are the most reliable models. © The Author(s).
The purpose of this preliminary study is to verify the possibility of using Iraqi Zahdi date palm biomass as a resource for biogas production, methane in particular using thermophilic anaerobic digestion with waste water treatment activated sludge. Moreover, is to investigate the influence of extra nutrients addition to the digestion mixture. Biogas was captured in sealed jars with remote sensing modules connected to computer with integrated program to record the gas pressure continuously. A total gas pressure with 67% Methane was produced from date pulp waste fermentation with a yield of 0.57 Lit for each gram volatile solid of substrate. Addition of 1% yeast extract solution as nutrient increased Methane yield in liters by 5.9%. This i
... Show MoreDate palm fiber is one of the common wastes available in the M. E. countries essentially Iraq. The aim of search to investigate the performance and effects of fiber date palm on the mechanical properties of high strength concrete, this fiber was used in three ratio 2, 4 and 6 % by vol. of concrete at ages of (7, 28, 90) days. Results demonstrated improvement in the compressive strength increased 19.2 %, 23.6%, 24.9 % for 2%, 4%, 6% of fiber respectively at age 28 days. Flexural strength increases 47.6%, 66.2%, 93.8% form (2,4,6) % of fiber respectively at age 28 days. Density increase about 0.41%, 0, 61 % 0.69 % for (2,4,6) % of fiber respectively at age 28. Absorption water decrease
This work predicts the effect of thermal load distribution in polymer melt inside a mold and a die during injection and extrusion processes respectively on the structure properties of final product. Transient thermal and structure models of solidification process for polycarbonate polymer melt in a steel mold and die are studied in this research. Thermal solution obtained according to solidify the melt from 300 to 30Cand Biot number of 16 and 112 respectively for the mold and from 300 to 30 Cand Biot number of 16 for die. Thermal conductivity, and shear and Young Modulus of polycarbonate are temperature depending. Bonded contact between the polycarbonate and the steel surfaces is suggested to transfer the thermal load. The temperat
... Show MoreAnomaly detection is still a difficult task. To address this problem, we propose to strengthen DBSCAN algorithm for the data by converting all data to the graph concept frame (CFG). As is well known that the work DBSCAN method used to compile the data set belong to the same species in a while it will be considered in the external behavior of the cluster as a noise or anomalies. It can detect anomalies by DBSCAN algorithm can detect abnormal points that are far from certain set threshold (extremism). However, the abnormalities are not those cases, abnormal and unusual or far from a specific group, There is a type of data that is do not happen repeatedly, but are considered abnormal for the group of known. The analysis showed DBSCAN using the
... Show MoreThis study presents a rapid, sensitive, and straightforward approach to measure chlorpheniramine maleate (CPM) by using turbidity CFIA. The method involves CPM reacting with sodium nitroprusside (Nitropress) to produce a pale white precipitate. The NAG-SSP-5S1D analyzer was used to measure turbidity at 0°–180° angle to detect the attenuation of incident light as a result of collision on the surfaces of the precipitate particles. The linear range of CPM measurements was between 0.008 and 11 m.mol/L, with correlation coefficient of 0.9983 and R2% = 99.65. The limit of detection was determined to be 0.0328 µg/sample from the lowest concentration in the calibration curve, and the repeatability of the method (RSD%) was less than 0.4% (n = 6
... Show MoreSemantic segmentation is an exciting research topic in medical image analysis because it aims to detect objects in medical images. In recent years, approaches based on deep learning have shown a more reliable performance than traditional approaches in medical image segmentation. The U-Net network is one of the most successful end-to-end convolutional neural networks (CNNs) presented for medical image segmentation. This paper proposes a multiscale Residual Dilated convolution neural network (MSRD-UNet) based on U-Net. MSRD-UNet replaced the traditional convolution block with a novel deeper block that fuses multi-layer features using dilated and residual convolution. In addition, the squeeze and execution attention mechanism (SE) and the s
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