One of the first signs Alzheimer's disease (AD) is mild cognitive impairment (MCI), in which there are small variants brain changes among intermediate stages. Although has been an increase research into diagnosis AD its early levels developments lately, changes, and their complexity for functional magnetic resonance imaging (fMRI), makes detection difficult. This paper proposes a deep learning-based method that can predict MCI, MCI (EMCI), late (LMCI), AD. The Disease Neuroimaging Initiative...

Alzheimer's disease (AD) is a neurodegenerative that affects brain cells, and mild cognitive impairment (MCI) has been defined as the early phase describes onset of AD. Early detection MCI can be used to save patient cells from further damage direct additional medical treatment prevent its progression. Lately, use deep learning for identification AD generated lot interest. However, one limitations such algorithms their inability identify changes in functional connectivity network patients...

Alzheimer’s disease (AD) has become a serious hazard to human health in recent years, and proper screening diagnosis of AD remain challenge. Multimodal neuroimaging input can help identify the early mild cognitive impairment (EMCI) late (LMCI) stages from normal development using magnetic resonance imaging (MRI) positron emission tomography (PET). MRI provides useful information on brain structural abnormalities, while PET data provide difference between physiological pathological changes...

Abstract Purpose Alzheimer’s disease (AD) is a progressive, incurable human brain illness that impairs reasoning and retention as well recall. Detecting AD in its preliminary stages before clinical manifestations crucial for timely treatment. Magnetic Resonance Imaging (MRI) provides valuable insights into abnormalities by measuring the decrease volume expressly mesial temporal cortex other regions of brain, while Positron Emission Tomography (PET) measures glucose concentration...

Stroke is a major cause of death worldwide, resulting from blockage in the flow blood to different parts brain. Many studies have proposed stroke disease prediction model using medical features applied deep learning (DL) algorithms reduce its occurrence. However, these pay less attention predictors (both demographic and behavioural). Our study considers interpretability, robustness, generalisation as key themes for deploying domain. Based on this background, we propose use random forest...

Multimodal neuroimaging has gained traction in Alzheimer’s Disease (AD) diagnosis by integrating information from multiple imaging modalities to enhance classification accuracy. However, effectively handling heterogeneous data sources and overcoming the challenges posed multiscale transform methods remains a significant hurdle. This article proposes novel approach address these challenges. To harness power of diverse data, we employ strategy that leverages optimized convolution techniques....

Alzheimer's disease (AD) is a neurological condition that gradually weakens the brain and impairs cognition memory. Multimodal imaging techniques have become increasingly important in diagnosis of AD because they can help monitor progression over time by providing more complete picture changes occur AD. Medical image fusion crucial it combines data from various modalities into single, better-understood output. The present study explores feasibility employing Pareto optimized deep learning...

Traffic law violation has been recognized as a major cause for road accidents in most parts of the world with majority occurring developing countries. Even presence rules and regulations stipulated against this, violators are still on increase. This is due to fact that not properly enforced by appropriate authorities those world. Therefore, system needs be designed assist enforcement agencies impose these improve safety reduce accidents. work uses Vehicle Plate Number Recognition (VNPR)...

Application layer or Layer Seven Distributed Denial of service (L7DDoS) intrusion is one the greatest threats that a webserver. The hackers have different motives which could be for Extortion, Exfiltration e.t.c Researchers employed several methods to prevent L7DDoS especially using machine learning. Although Machine learning techniques has proven very effective with high detection accuracy, approach still find it difficult detect Hyper Text Transfer Protocol (HTTP) based botnet traffic on...

This paper demonstrates the robustness of active queue management techniques to varying load, link capacity and propagation delay in a wireless environment. The performances four standard controllers used Transmission Control Protocol/Active Queue Management (TCP/AQM) systems were compared. Fixed-Parameter Proportional Integral (PI), Random Early Detection (RED), Self-Tuning Regulator (STR) Model Predictive (MPC). congestion control algorithm each technique was documented by simulating...

Summary Background One of the significant attacks targeting application layer is distributed denial‐of‐service (DDoS) attack. It degrades performance server by usurping its resources completely, thereby denying access to legitimate users and causing losses businesses organizations. Aim This study aims investigate existing methodologies for application‐layer DDoS (APDDoS) attack defense using specific measures: detection methods/techniques, strategy, feature exploration APDDoS mechanisms....

ABSTRACT Multimodal neuroimaging, combining data from different sources, has shown promise in the classification of Alzheimer's disease (AD) stage. Existing multimodal neuroimaging fusion methods exhibit certain limitations, which require advancements to enhance their objective performance, sensitivity, and specificity for AD classification. This study uses use a Pareto‐optimal cosine color map performance visual clarity fused images. A mobile vision transformer (ViT) model, incorporating...

Cloud computing is a paradigm that uses utility-driven models in providing dynamic services to clients at all levels. Performance analysis and modelling essential because of service level agreement guarantees. Studies on performance are increasing productive manner the cloud landscape issues like virtual machines data storage. The objective this study conduct systematic mapping systems applications. A useful visualization summarizing research carried an area interest. provided overview...