Latest Essays
A Multi-Core-Multi Objective Based Artificial Intelligence With A Hybrid Meta-Heuristic Based Core Prediction And Resource Allocation
Abstract Asymmetric Multicore Processors (AMP) are becoming used in both advanced and basic computing systems due to their fundamental flexibility and outstanding computing possibilities. Among the subcategories of AMP, Performance Asymmetric Multicore (PAM) Architectures are unique in that they include various micro-architecture cores into a single chip. Nevertheless, the complex interplay between heterogeneous cores and a diverse range of applications presents a formidable challenge in determining the optimal hardware configuration,
A Novel Approach Based On Fuzzy Rule And LSOWL-CNN Forecasting Students With Dropout Prediction And Recommendation Model
Abstract Governments are primarily concerned with ensuring that all citizens of the world have access to education regardless of their disabilities. This article presents a method for predicting dropout rates among disabled students in order to offer recommendations and alternative pathways for their career enhancement. To achieve this, data on training students’ learning behaviour was collected through an online survey completed by various student organizations, both dropout and non-dropouts. The
Fuzzy Neural Network Application For Determining The Presence Of Social Media Consumption
Abstract A decision-making model for social media addiction is established. Fuzzy mathematics and BP neural networks are used in the model. There are chosen six judging directories. Quantitative directories’ subsidiary grade functions are organised. Expert scoring confuses the qualitative directories. College students who use networks are randomly chosen as samples. The trial demonstrates that the procedure could effectively and accurately carry out the choice on Social Media dependence. Introduction Experts
Using Apache Hadoop And Hybrid Deep Learning For Gene-Based Disease Prediction In Healthcare
Abstract Advancements in genetic research have opened up new avenues for understanding and predicting genetic disorders. This study presents a comprehensive pipeline for gene-based disease prediction, leveraging big data and deep learning techniques. The study employs Apache Hadoop-based big data handling to efficiently process and manage the voluminous and intricate genetic datasets. The collected genetic data then undergoes meticulous pre-processing, which involves crucial steps such as data cleaning, standardization, and
Role Of Social Identity Signalling In Brand Tribalism Of Generational Cohorts
Abstract This research delves deep into the complex interaction between brand loyalty and social identity signalling across generations. People now look to brands more than ever before to convey who they are and where they fit in the ever-changing consumer environment. This study delves into what drives brand loyalists’ need to broadcast their social identities via their chosen brands. The complex ways in which different generations interact with brands as
Opportunities And Benefits Of Artificial Algorithms
3.1 Introduction Artificial Intelligence (AI) refers to the emulation of human cognitive abilities in machines imbued with the capacity to engage in logical thinking and exhibit behaviours reminiscent of those displayed by humans. This encompasses the creation of algorithms and computer programs that possess the capability to execute activities which generally necessitate human intellect (Strong, 2016) (Davenport, 2018), including visual cognition, speech identification, decision-making, and linguistic translation. AI harbours the
Adapting Jeans Production To Evolving Consumer Preferences
3.1 Introduction In the rapidly changing world of jeans production, comprehending and aligning with evolving consumer preferences and market trends is of utmost importance for ensuring long-lasting success [1]. This study delves into the intricate fabric of the industry with the aim of unravelling the subtle interplay between consumer choices and the ever-changing demands of fashion. As denim enthusiasts continually seek innovative styles and sustainable options, manufacturers must navigate a
Fabrication And Evaluation Of Chitosan-Based Electrospun Nanofibers Loaded With Environmentally Synthesized Silver Nanoparticles For Enhanced Wound Healing
Abstract The use of electrospinning to create dressings for wounds has gained more scientific attention over the past few years. In addition to the method’s ease of use, versatility, and scalability, the electrospun nanofiber produced has extraordinary characteristics extraordinary characteristics such as the ability to absorb wound exudate, flexibility, high porosity, and a high surface-to-volume ratio. This study aims to synthesize and characterize chitosan-based electrospun nanofibers that are rich in
A Multi-Level Fuzzy Aware Denoising Technique With A Gradiant Enhanced Convolution Network With Dual Level Classifier For Detecting And Classifying Psoriasis Disease
Abstract Skin disorders have a reduced mortality rate than other diseases, but because they cause sensations like pain, discomfort, and itching, they have a bigger influence on quality of life. One of the common skin conditions that is immune-mediated and chronically inflammatory is psoriasis. According to estimates, 1.8 billion individuals worldwide have some kind of skin illness. Proper examination at the right time helps better. There are various methods in
WebAR In E-Commerce
Chapter 1 Introduction 1.1 Introduction to Augmented Reality (AR) and its Evolution The commerce landscape has been transformed by technology, pushing businesses to innovate and engage with consumers. Augmented Reality (AR) is a recent technological advancement with significant potential (Guinan et al., 2019). AR combines real and virtual worlds in operations. It enhances electronic commerce by improving how products are displayed, experienced, and purchased. WebAR enables AR experiences in web browsers,
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