Latest Essays
Enhancing Urban Safety With Automated Crime Anomaly Detection Using Ensembled Deep Learning In Smart Cities
Abstract In the context of smart cities, ensuring safety and security is paramount, and the increasing deployment of surveillance cameras presents both an opportunity and a challenge. This paper introduces an automated Crime Anomaly Detection System (CADS) that harnesses the capabilities of Deep Learning (DL) and computer vision to address this challenge. CADS follows a systematic workflow, starting with the collection of video data from smart city surveillance cameras. It
Analysis Of ECG Signals For Ischemic Heart Disease Prediction Using Optimized Artificial Neural Network
Introduction The most prevalent dangerous illness is thought to be heart attacks. Medical practitioners perform numerous surveys on heart disease to acquire data on the illnesses, symptoms, and course of the condition [1]. Since cardiovascular disease is the most predictable disease in the world, it is a major worry for the medical sector in today’s heart disease research. Scaling down small and amazing gadgets that may be utilised while calculating
Secure Transfer Of Data In Cloud Computing Using DNA Cryptography With Cipher Techniques
Abstract Cloud computing is a type of distributed computing that allows organizations to store and access data on-demand. It is commonly used for various applications such as network services, storage, and platform services. However, many organizations are not excited about using it due to security concerns. Various researchers have been developing various methods to improve the security of cloud computing. One of these is the Bi-directional DNA encryption algorithm. However,
A Review Of Integration Of Fiber Bragg Grating Sensors In The Fourth Industrial Revolution (FBG-4IR)
Abstract Review of the Fiber Bragg Grating (FBG) sensor technology’s state-of-the-art. In the past three decades, FBG sensors have drawn a lot of attention because of their key benefits, which include immunity to electromagnetic interference, lightweight, compact size, high sensitivity, huge operation bandwidth, and excellent multiplexing capabilities. Temperature and strain are the two most extensively researched sense physical variables. This paper focuses on the operation of fiber bracket grating sensors
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
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