Physicians are likely to expend significant labor and time while manually calculating blood smears. Automatic computer-based methods for classifying acute lymphoblastic leukemia have trouble correctly lighting stained white blood cell microscopy images and accurately separating cells that touch or overlap. Additionally, incorporating machine learning techniques into medical services is very hard because doctors can deal with rough guesses as long as the results aren't too bad, but they can't use these calculations for actual medical care. Enabling a A deep network having knowledge of the accuracy of its own predictions is a fascinating and crucial issue. Most instances segmentation frameworks weigh the mask quality during the instance segmentation process based on classification confidence. Here, we consider the context of this problem and present Mask Cell of multi-class deep network (MCNet) as a new network that has the module to learn about the quality of the predicted instance masks. Our proposal entails using faster R-CNN, such as segmentation on white blood cell microscope images, to accurately categorize acute lymphoblastic leukemia cases. This approach aims to enhance the efficiency and effectiveness of the diagnostic process. The suggested network block combines the instance feature with the matching anticipated mask to estimate the proposed mask IoU. In this work, we used the transfer learning approach to apply Mask R-CNN to segment white blood cells on a microscope image. To address the issue of poor lighting in stained white blood cell microscopy pictures, We included a contrast enhancement procedure in the image dataset. The comparative experiment applies YOLO v9 for classification and Mask R-CNN. The MCNet approach adjusts the discrepancy between the quality of the mask and its proposed detection, enhancing the effectiveness of instance segmentation. The final results for two datasets trained using PBC and BCCD are as follows: the accuracy of mAP@IoU 0.50 for the PBC dataset is 95.70, while the Accuracy for the BCCD dataset is 96.76, with recall and precision both coming in at 97.23 and 96.72, respectively.
Mammalian cell culture refers to culturing mammalian cells in a medium that provide nutrients for cells to be able to grow in vitro under environment that closely mimic the in vivo conditions. By enabling culturing these cells outside living biological entities, investigation on intra- and intercellular activities and flux; genetic and phenotyping analysis; proteomics, study of toxicology, drug discovery and development can be carried out without manipulation of living animals. In this chapter, detail protocol of media preparation, cell culture maintenance and preservation are elaborated for both types of mammalian cell culture, monolayer or suspension cultures. Determination of number of cells is discussed as well.
Songs are considered as an educational and a substantial dependable references used in teaching and learning, particularly the so - called foreign language learning that allows learners to adapt to the target language culture and to develop their language learning skills including: listening comprehension, reading comprehension, speaking and writing. Consequently, it can be said that the Francophone songs with the musical richness and resonance specifically facilities French language learning skills for all levels of education and achieve short and long terms predetermined educational language learning goals.
In fact, language learning through songs method does not only include the
... Show MoreWithin this paper, we developed a new series of organic chromophores based on triphenyleamine (TPA) (AL1, AL-2, AL-11 and AL-22) by engineering the structure of the electron donor (D) unit via replacing a phenyle ring or inserting thiophene as a π-linkage. For the sake of scrutinizing the impact of the TPA donating ability and the spacer upon the photovoltaic, absorptional, energetic, and geometrical characteristic of these sensitizers, density functional theory (DFT) and time-dependent DFT (TD-DFT) have been utilized. According to structural characteristics, incorporating the acceptor, π-bridge and TPA does not result in a perfect coplanar conformation in AL-22. We computed EHOMO, ELUMO and bandgap (Eg) energies by performing frequency a
... Show MoreIntrusion detection systems detect attacks inside computers and networks, where the detection of the attacks must be in fast time and high rate. Various methods proposed achieved high detection rate, this was done either by improving the algorithm or hybridizing with another algorithm. However, they are suffering from the time, especially after the improvement of the algorithm and dealing with large traffic data. On the other hand, past researches have been successfully applied to the DNA sequences detection approaches for intrusion detection system; the achieved detection rate results were very low, on other hand, the processing time was fast. Also, feature selection used to reduce the computation and complexity lead to speed up the system
... Show MorePattern matching algorithms are usually used as detecting process in intrusion detection system. The efficiency of these algorithms is affected by the performance of the intrusion detection system which reflects the requirement of a new investigation in this field. Four matching algorithms and a combined of two algorithms, for intrusion detection system based on new DNA encoding, are applied for evaluation of their achievements. These algorithms are Brute-force algorithm, Boyer-Moore algorithm, Horspool algorithm, Knuth-Morris-Pratt algorithm, and the combined of Boyer-Moore algorithm and Knuth–Morris– Pratt algorithm. The performance of the proposed approach is calculated based on the executed time, where these algorithms are applied o
... Show MoreTerahertz (THz) technology, which uses radiation lying between microwave and infrared in the electromagnetic spectrum, could revolutionize digital agriculture through terahertz’s ability to assess agricultural materials accurately and non-destructively. The review discusses notable developments in THz applications to digital agriculture: real-time crop monitoring, nutrient and disease detection, soil moisture and contaminant analysis, and supply chain traceability. The developments have emerged from studies in time-domain spectroscopy, imaging, machine learning (ML), and blockchain integration. Despite the promising advances in THz agricultural applications, limitations remain, such as limited penetration depth, high system costs, and ope
... Show MoreThe proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue
... Show MoreThe present study aimed at shed light on the association between HLA-class I antigens (A, B and Cw) and brain tumours (meningioma and glioma) in the basis of their individual frequencies or two-locus association A total of 52 brain tumour patients were enrolled in this study, with an age range of 7-68 years. The patients were divided into two clinical groups; meningioma (20 cases) and glioma (22 cases), while the remaining 10 cases represented other types of brain tumour. Control samples included 47 Iraqi Arab apparently healthy blood volunteers, with an age range of 15-50 year. Three HLA antigens showed a significant increased frequency in total patients as compared to controls. They were B13 (34.6 vs. 6.5%), B40 (15.4 vs. 2.2%) and Cw3
... Show MoreThe aims of this study are to explore the commercial artifacts in the following three kinds of vegetables oils, Nigella Sativa, Trigonella foenum-graecum Linn,and Zingiber officinale. These oils have been very popular medicinal plants which are commonly used in traditional medicine .These commercial oils have been compared with the extracts of these plants.
The physical properties of extracts and commercial oils of these plants have been stuied. We observed that the refractive index of the plants matches and non-significant, while specific gravity of Nigella Sativa has similar specific gravity in both extracts and commercial oil in contrast with Trigonella foenum Linn,and Zingiber officinale and we found significant difference (P<