COMPUTING TRENDZ

Machine Learning Algorithms for Image Classification: A Comparative Review

Basu Dev Shivahare — 2024-10-25

In the realm of computer vision, one of the most important challenges is image categorization. Its goal is to assign semantic labels to photographs based on a predetermined set of categories, and it does this via a process called semantic labeling. In attempt to find a solution to this issue, several distinct machine learning algorithms have been developed throughout the course of time; each strategy has its own unique mix of benefits and drawbacks. This article gives an in-depth review and comparison of a wide variety of well-known machine learning approaches for the classification of pictures. This review covers a wide range of algorithms, including more traditional approaches such as Support Vector Machines (SVMs), Convolutional Neural Networks (CNNs), and Transfer Learning using pretrained models such as VGG, Reset, and Inception.

Current Trends in ICT Security: A Comprehensive Overview of Machine Learning and Soft Computing Applications

Himanshu Hora — 2024-10-25

In an era marked by pervasive digitization, information and communication technology (ICT) security stands as a cornerstone of our digital infrastructure. The rapid evolution of cyber threats necessitates equally agile defence mechanisms. This research paper provides a comprehensive overview of the contemporary landscape of ICT security with a specific focus on the emergent trends in machine learning (ML) and soft computing (SC) applications.

The paper commences by outlining the escalating challenges posed by cyber adversaries, underlining the inadequacy of traditional security paradigms in contending with the intricacies of modern-day attacks. This backdrop emphasizes the need for innovative, adaptable, and intelligent approaches to bolster ICT security.

Enhancing Robo-Advisors: A Study of Personalized Financial Planning Through AI-Driven Insights

Tanwangini Sahani — 2024-10-25

The emergence of robo-advisors has revolutionized the financial advisory field, presenting automated investment suggestions tailored to individual investors' distinct goals and risk appetites. This research paper aims to explore the dynamic evolution of robo-advisory services, delving into the ways artificial intelligence (AI) and data-derived insights can be harnessed to provide an even more personalized and efficient financial planning encounter. Through an exploration of advanced algorithms, machine learning methodologies, and user-centered design concepts, this investigation strives to uncover the techniques robo-advisors use to refine their decision-making procedures, accommodating the distinct financial ambitions of each investor. By means of practical analyses, illustrative case studies, and a discerning assessment of industry tendencies, this research illuminates the obstacles and prospects inherent in attaining genuine personalization within the domain of automated financial guidance.

A comprehensive analysis of security mechanism for CSMA/CD Networks: A Survey

Shubham Singh — 2024-10-25

In this essay, we examine security against several types of harmful assaults. We also include several known practicable assaults in this. We also learn about secure communication for various mechanisms that offer confidentiality, security, and authentication for the majority of security concerns. An active repeater in CSMA/CD for network comparison for data transfer between two addresses is what we learn about in a logical part. If there is no match, the logic portion instructs the transmitter to switch from broadcasting the data packet to transmitting the clock signal. Bidirectional routing messages are sent from the wireless network to the wired network.At the conclusion, we receive comparison results for the transmitted and received messages to determine if a collision has happened.

A Detailed Analysis on Evaluation of Green Computing

Sushil Kumar Mishra — 2024-10-25

Abstract: Currently, computers are not only used in offices but utilized at home as well. The amount of energy consumed by the growing daily use of computers contributes to a rise in the atmosphere's carbon content. The IT sector is mostly to blame for 3% of the world's energy usage, which is rising by 20% annually. These days, green computing is a very emerging topic today. He is responsible for the use of computers and associated resources. It encompasses the application of energy efficient processors, servers and peripherals, along with less resource usage and appropriate electronic waste disposal waste. Enhancing the life cycle efficiency of IT devices and approving the recycling of wasteful items and manufacturing waste are the main objectives of green computing. The methods for conserving green energy and their potential applications are discussed in this article. By "aligning all IT processes and practices with the core principles of sustainability, which are to reduce, reuse, and recycle; and finding innovative ways to use IT in business processes to deliver sustainability benefits across the enterprise and beyond," green computing can also create beneficial solutions. Green computing and green chemistry share many of the same objectives, including minimizing the use of hazardous materials, optimizing energy efficiency over the course of a product's lifetime, and fostering the recyclable or biodegradable nature of factory waste and non-operational products .