The first function of the system is to detect the presence of obstacles. When the user activates the system using the power ON/OFF switch, the Arduino microcontroller will read the data. When the ultrasonic sensor detects the presence of an obstacle in the process of moving forward, the robot will move backward.

A subfield of artificial intelligence called "machine learning" enables computers to learn from data without explicit human programming. In a broad sense, artificial intelligence (AI) refers to any computer or system behavior that resembles human behavior.

Facial expression recognition (FER), a computer vision problem, tries to identify and classify the many expressions of emotion that can be detected on a person's face. One of the largest challenges to face recognizing and identification is the extraordinary variety of human faces in terms of size, shape, position, illumination, expression, and occlusion.

In this research, we will first introduce the science of plasmonics and then we will examine plasmonic sensors. us to make a suitable and better quality sensor by changing part of their structure than the previous sensors. Plasmonic sensors have a simple frame and high optical resolution and are able to transmit and guide plasmonic waves.

Text summarising is a method for taking the most crucial information from various texts, compressing it, and keeping the text's overall meaning. Rarely does one need to read reams of documentation to get the gist of a topic; frequently, a brief synopsis is adequate.

This technology came into prominence during Big Data and Real-Time Analytics and also forms an essential component of Modern Computer Architecture. Using CDC, real-time changes in the source tables can be captured and processed thus allowing for integrating the changes into target systems or offering timely updates.

Artificial Intelligence (AI) has introduced significant advancements in operational efficiency across various domains, including IT Service Management. A crucial aspect of this field is the resolution process, which involves addressing issue tickets that represent interactions between IT agents and problem holders. Traditionally, these tickets are manually categorized to facilitate continuous improvement and proper escalation within the support team.

In today's world, where the business environment changes every day, AI, together with BI, changes the decision-making process. This paper delves into the role and impact AI is having on traditional business analytics through BI that is driven by AI and what new concepts it brings to traditional business analytics, including accurate and real-time insight provision, enabler of predictive analysis and automation of data-intensive tasks.

This article presents a comprehensive comparative analysis of various neural network architectures employed in deep reinforcement learning (DRL). We examine the efficacy, computational complexity, and scalability of different architectures, including feedforward networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformer-based models. Our study encompasses both value-based and policy-gradient methods, evaluating their performance across a spectrum of environments and tasks.

Based on the introductory framework, this research focuses on the use of AI in forecasting market volatility, an essential component of risk management in financial markets. The results of using different machine learning models for predicting the stock price with the help of historical data are also described. Thus, the results suggest the use of AI’s ability to improve predictive power and, thereby, offer valuable insights for investors and financial organizations.

Automation using Microsoft Power Platform is transforming the way organizations operate by streamlining processes, enhancing productivity, and reducing manual intervention. The Power Platform, which includes Power Apps, Power Automate, Power BI, and Power Virtual Agents, enables users to automate workflows, build custom apps, analyze data, and create intelligent chatbots with minimal or no coding skills. This accessibility empowers both technical and non-technical users to develop tailored solutions that meet their specific business needs.

This paper aims to establish the fact that AMR is one of the biggest challenges that public health is facing in the 21st century. The emergence of new resistant bacterial strains has dampened the effectiveness of the available antibiotic drugs, hence making it necessary to look for new approaches that may help in the development of new antibiotics. Due to the complexity of the problem, new and well-developed means of machine learning based on artificial intelligence and data analysis have appeared.

DFMEA and PFMEA are crucial methodologies applied in the design for and manufacture of safety and reliability in product development. The analyses prevent defects and reduce risks in products by spotting potential failure modes early in the design and production process, hence generally improving the quality of such products. This paper discusses the application of DFMEA and PFMEA in ensuring product safety and reliability and meeting industrial standards.

A number of changes have been experienced in the advertising industry because of the introduction of artificial intelligence (AI). The combination of WP predictive analysis and deep consumer personalization is transforming the way that brands actively engage the consumer. This paper analyses how these advanced AI techniques are interconnected in creating effectual advertising strategies. Predictive analytics use past data obtained earlier in order to predict the actions and purchase decisions of the consumer.

The drive towards ever-smaller and more complex semiconductor designs brings significant challenges for ensuring accuracy and manufacturability. This paper explores the evolving landscape of physical verification techniques in 2023, examining how the industry is adapting to these challenges. It investigates the rising use of machine learning to analyze complex design data, the adoption of cloud computing to manage the growing computational burden, and the increasing importance of formal verification methods for guaranteeing design correctness.

The pandemic has made companies adopt remote work policies and convert to cloud-based technologies. This adoption has helped the companies to continue the business without disruption, but this has also increased the risks for the companies. One of the critical risks among them is Insider Threats. Due to the Remote work option, employees can access the data without any surveillance monitoring.