Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN, YOLO, and SSD for effective drone detection in various environments. We have found that both Faster RCNN and YOLO have high recognition ability compared to SSD; on the other hand, SSD has good detection ability.
Triticale is a hybrid of wheat and rye grown for use as animal feed. In Florida, due to its soft coat, triticale is highly vulnerable to Sitophilus oryzae L. (rice weevil) and there is interest in development of methods to detect early-instar larvae so that infestations can be targeted before they become economically damaging. The objective of this study was to develop prediction models of the infestation degree for triticale seed infested with rice weevils of different growth stages. Spectral signatures were tested as a method to detect rice weevils in triticale seed. Groups of seeds at 11 different levels (degrees) of infestation, 0–62%, were obtained by combining different ratios of infested and uninfested seeds. A spectrophotometer wa
... Show Morethe study including isolation and identification of candida spp causing UTIs from patintes coming to al-yarmouk hospital
Linear programming currently occupies a prominent position in various fields and has wide applications, as its importance lies in being a means of studying the behavior of a large number of systems as well. It is also the simplest and easiest type of models that can be created to address industrial, commercial, military and other dilemmas. Through which to obtain the optimal quantitative value. In this research, we dealt with the post optimality solution, or what is known as sensitivity analysis, using the principle of shadow prices. The scientific solution to any problem is not a complete solution once the optimal solution is reached. Any change in the values of the model constants or what is known as the inputs of the model that will chan
... Show More98 samples were collected from various clinical sources included (Burns, wounds, urines, sputums, blood) From the city of Baghdad, After performing the biochemical and microscopic examination, 52 isolates were obtained for Pseudomonas aeruginosa, 17 (32.7%) isolates from burn infection, 12 (23%) isolates from Wound infection 11 (21.2%) isolates from urine infection, 7 (13.5%) isolates of sputum and 5 (9.6%) isolates from blood. Bacteria susceptibility to form biofilm has been detectedby microtiter plate method, The results showed that 80% of the bacterial isolates were produced the biofilm with different proportions, alg D gene (alginate production) has been detected by polymerase chain reaction (PCR) Which plays an essential role in the fo
... Show MoreThe aims of the present study are to evaluate the levels of CA19-9 in sera and tissues' homogenate of breast and thyroid benign patients in order to assess its use as an early diagnostic parameter in differentiation between malignant and benign cases. The study was conducted on 8 patients with breast benign tumor and 8 patients with thyroid benign tumor, by the enzyme linked immunosorbent assay (ELISA) technique. The results of CA19-9 levels in sera were (15 ±1.58 and 10.67 ±2.08)U/ml respectively compared with serum CA19-9 levels of control group which was 7.74 ±4.92 U/ml, the results were found to be highly significantly in breast tumor patients and non significantly in thyroid
... Show MoreThe brain's magnetic resonance imaging (MRI) is tasked with finding the pixels or voxels that establish where the brain is in a medical image The Convolutional Neural Network (CNN) can process curved baselines that frequently occur in scanned documents. Next, the lines are separated into characters. In the Convolutional Neural Network (CNN) can process curved baselines that frequently occur in scanned documents case of fonts with a fixed MRI width, the gaps are analyzed and split. Otherwise, a limited region above the baseline is analyzed, separated, and classified. The words with the lowest recognition score are split into further characters x until the result improves. If this does not improve the recognition s
... Show MoreThis study was aimed to use plant tissue culture technique to induce callus formation of Aloe vera on MS. Medium supplied with 10 mg/l NAA and 5 mg/l BA that exhibit the best results even with subculturing. As the method of [1] 1g. dru weight of callus induced from A. vera crown and in vivo crown were extracted then injected in HPLC using the standards of Ascorbic acid (vit. C), Salysilic acid and Nicotenic acid (vit. B5) to compare with the plant extracts. Results showed high potential of increasing some secondary products using the crown callus culture of A. vera as compared with in vivo crown, Ascorbic acid was 1.829 ?g/l in in vivo crown and increased to 3.905 ?g/l crown callus culture . Salysilic acid raised from 3.54 ?g/l in in vivo c
... Show MoreSome of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems. Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic. Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance. In this study, two different sets of select
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