Optimizing Alzheimer's disease prediction using the nomadic people algorithm

The problem with using microarray technology to detect diseases is that not each is analytically necessary. The presence of non-essential gene data adds a computing load to the detection method. Therefore, the purpose of this study is to reduce the high-dimensional data size by determining the most critical genes involved in Alzheimer's disease progression. A study also aims to predict patients with a subset of genes that cause Alzheimer's disease. This paper uses feature selection techniques like information gain (IG) and a novel metaheuristic optimization technique based on a swarm’s algorithm derived from nomadic people’s behavior (NPO). This suggested method matches the structure of these individuals' lives movements and the search for new food sources. The method is mostly based on a multi-swarm method; there are several clans, each seeking the best foraging opportunities. Prediction is carried out after selecting the informative genes of the support vector machine (SVM), frequently used in a variety of prediction tasks. The accuracy of the prediction was used to evaluate the suggested system's performance. Its results indicate that the NPO algorithm with the SVM model returns high accuracy based on the gene subset from IG and NPO methods

The Use Of Spatial Relationships And Object Identification In Image Understanding

Image understanding includes mathematical and geometrical abilities.It requires analyzing,classifying,labeling to identify requirements,involving difference comparing or appreciated gaps in an image or object analysis,and these investigation cases use different methods.Image understanding supports many knowledge fields as Image Processing,Artificial Intelligence,Computer Graphics, Psychology,Object Recognition and many other fields.From another side,the information of spatial relationships holds enormous and vast inputs for the study of image understanding.This paper concentrated on the techniques of image understanding by the use of spatial relationships and object identification,whereas staying nearer to the related issues

Using Machine Learning via Deep Learning Algorithms to Diagnose the Lung Disease Based on Chest Imaging: A Survey

— Chest imaging diagnostics is crucial in the medical area due to many serious lung diseases like cancers and nodules and particularly with the current pandemic of Covid-19. Machine learning approaches yield prominent results toward the task of diagnosis. Recently, deep learning methods are utilized and recommended by many studies in this domain. The research aims to critically examine the newest lung disease detection procedures using deep learning algorithms that use X-ray and CT scan datasets. Here, the most recent studies in this area (2015-2021) have been reviewed and summarized to provide an overview of the most appropriate methods that should be used or developed in future works, what limitations should be considered, and at what level these techniques help physicians in identifying the disease with better accuracy. The lack of various standard datasets, the huge training set, the high dimensionality of data, and the independence of features have been the main limitations based on the literature. However, different architectures of deep learning are used by many researchers but, Convolutional Neural Networks (CNN) are still state-of-art techniques in dealing with image datasets

Early Alzheimer's Disease Detection Using Different Techniques Based on Microarray Data: A Review

Alzheimer's Disease (AD) is a degenerative disease of the brain that results in memory loss due to the death of brain cells. Alzheimer's disease is more common as people get older. Memory loss happens over time, and as a result, the person loses the ability to react appropriately to their surroundings. Microarray technology has emerged as a new trend in genetic research, with many researchers utilizing it to look at the changes in gene expression in particular organisms. Microarray experiments can be used in various ways in the medical field, including the prediction and detection of disease. Large amounts of unprocessed raw gene expression profiles sometimes contribute to computational and analytic difficulties, including selecting dataset features and classifying them into an appropriate group or class. The large dimensions, lesser sample size, and noise in gene expression data make it difficult to attain good Alzheimer classification accuracy using the entire collection of genes. The categorization process necessitates careful feature reduction. As a result, a comprehensive review of microarray Alzheimer's disease studies is presented in this paper, focusing on feature selection techniques

Applying the MCMSI for Online Educational Systems Using the Two-Factor Authentication

 This paper researches the evolution process of what is called two-factor authentication technique and its adaptation related to the educational system through the Internet. This technique is a measure of security employed, particularly in scopes which have valuable information like bank services. It witnesses developments so far as today, in parallel with the developments occurring in technology. Since this technique consists of two phases, the security is going to be developed. Today, bank services, devices using the Internet of things, tickets of public transportation and lots of other scopes are utilized. In the information field, the researchers and scientists always update the techniques of two-factor authentication to resist the attacks related to security. Last years, the researchers studied novel technologies like behavioral biometric or biometrics. The training through the Internet may become much more useful than going to someplace to study a specific course. Mostly, the participants in the trainings through the Internet get many certificates for success, participation, etc. The principal problem is how to certify the truthiness of the participant who desires to get the certification. In this paper, and by researching the techniques of two-factor authentication, the Mimic Control Method with Sound Intensity (MCMSI) is proposed to be used for the training through the Internet