Today’s modern medical imaging research faces the challenge of detecting brain tumor through Magnetic Resonance Images (MRI). Normally, to produce images of soft tissue of human body, MRI images are used by experts. It is used for analysis of human organs to replace surgery. For brain tumor detection, image segmentation is required. For this purpose, the brain is partitioned into two distinct regions. This is considered to be one of the most important but difficult part of the process of detecting brain tumor. Hence, it is highly necessary that segmentation of the MRI images must be done accurately before asking the computer to do the exact diagnosis. Earlier, a variety of algorithms were developed for segmentation of MRI images by using different tools and techniques. However, this paper presents a comprehensive review of the methods and techniques used to detect brain tumor through MRI image segmentation. Lastly, the paper concludes with a concise discussion and provides a direction toward the upcoming trend of more advanced research studies on brain image segmentation and Tumor detection.
In this paper, RBF-based multistage auto-encoders are used to detect IDS attacks. RBF has numerous applications in various actual life settings. The planned technique involves a two-part multistage auto-encoder and RBF. The multistage auto-encoder is applied to select top and sensitive features from input data. The selected features from the multistage auto-encoder is wired as input to the RBF and the RBF is trained to categorize the input data into two labels: attack or no attack. The experiment was realized using MATLAB2018 on a dataset comprising 175,341 case, each of which involves 42 features and is authenticated using 82,332 case. The developed approach here has been applied for the first time, to the knowledge of the authors, to dete
... Show MoreDetermining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on
... Show MoreWith the growth of mobile phones, short message service (SMS) became an essential text communication service. However, the low cost and ease use of SMS led to an increase in SMS Spam. In this paper, the characteristics of SMS spam has studied and a set of features has introduced to get rid of SMS spam. In addition, the problem of SMS spam detection was addressed as a clustering analysis that requires a metaheuristic algorithm to find the clustering structures. Three differential evolution variants viz DE/rand/1, jDE/rand/1, jDE/best/1, are adopted for solving the SMS spam problem. Experimental results illustrate that the jDE/best/1 produces best results over other variants in terms of accuracy, false-positive rate and false-negative
... Show MoreReview of multidrug sensitivity and resistance in enterococcus
Schiff bases (SBs) represent multipurpose ligands that can be prepared from the concentration of prime amines with carbonyl clusters. Creation of SB transition metal compounds via as ligands has opportunity of attaining coordination complexes of abnormal arrangement and stability. These transition metal compounds have extraordinary attention as a consequence of their dynamic portion in metalloenzymes and as biomimetic prototypical complexes as a result of their proximity to usual enzymes and proteins. These complexes are imperative in medicinal disciplines owing to their widespread range of biological actions. They mostly exhibit organic actions involving antifungal, antibacterial, antitumor, antidiabetic, herbicidal, antiproliferative, ant
... Show MoreWith the exception of Antarctica, all continents are home to Echinococcus species. These parasite infections are thought to be quite dangerous, causing high rates of morbidity and mortality as well as large financial losses for the cattle sector from a human and veterinary standpoint, the two primary species to consider are Echinococcus granulosus sensu lato (s.l.) and Echinococcus multilocularis, which cause cystic echinococcosis (CE) and alveolar echinococcosis (AE), respectively. The present state-of-the-art knowledge on these two parasites is compiled in this study in four major areas that are pertinent to both human and veterinary professionals: diagnosis, treatment and prevention, clinical symptoms and pathogenesis, and transm
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