In recent years, artificial intelligence (AI) has emerged as a transformative force across various sectors of modern society, reshaping economic landscapes, social interactions, and ethical considerations. This paper explores the multifaceted impact...
The study comprehensively reviews artificial intelligence (AI) techniques for addressing algorithmic bias in job hiring. More businesses are using AI in curriculum vitae (CV) screening. While the move improves efficiency in the recruitment process, i...
Physics-informed neural networks (PINNs) represent a significant advancement at the intersection of machine learning and physical sciences, offering a powerful framework for solving complex problems governed by physical laws. This survey provides a c...
In modern life, the application of artificial intelligence (AI) has promoted the implementation of data-driven algorithms in high-stakes domains, such as healthcare. However, it is becoming increasingly challenging for humans to understand the workin...
Artificial intelligence (AI) is a rapidly growing technological phenomenon that all industries wish to exploit to benefit from efficiency gains and cost reductions. At the macrolevel, AI appears to be capable of replacing humans by undertaking intell...
Technical advancements within the subject of artificial intelligence (AI) leads towards development of human-like machines, able to operate autonomously and mimic our cognitive behavior. The progress and interest among managers, academics and the pub...
Situational awareness (SA) is defined as the perception of entities in the environment, comprehension of their meaning, and projection of their status in near future. From an Air Force perspective, SA refers to the capability to comprehend and projec...
Cryptocurrency is a new sort of asset that has emerged as a result of the advancement of financial technology and it has created a big opportunity for researches. Cryptocurrency price forecasting is difficult due to price volatility and dynamism. Aro...
Artificial Intelligence (AI) describes computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and language translation. Examples of AI techniques are machine le...
The technology acceptance model is a widely used model to investigate whether users will accept or refuse a new technology. The Metaverse is a 3D world based on virtual reality simulation to express real life. It can be considered the next generation...
Insect swarms and migratory birds are known to exhibit something known as a hive mind, collective consciousness, and herd mentality, among others. This has inspired a whole new stream of robotics known as swarm intelligence, where small-sized robots...
Retrieval-Augmented Generation (RAG) enhances large language models (LLMs) by integrating external knowledge retrieval to improve factual consistency and reduce hallucinations. Despite growing interest, its use in healthcare remains fragmented. This...
Transformer architectures are highly expressive because they use self-attention mechanisms to encode long-range dependencies in the input sequences. In this paper, we present a literature review on Transformer-based (TB) models, providing a detailed...
Detecting malignant lung nodules from computed tomography (CT) scans is a hard and time-consuming task for radiologists. To alleviate this burden, computer-aided diagnosis (CAD) systems have been proposed. In recent years, deep learning approaches ha...
Despite the focus on improving cybersecurity awareness, the number of cyberattacks has increased significantly, leading to huge financial losses, with their risks spreading throughout the world. This is due to the techniques deployed in cyberattacks...
Introduction: Deep reinforcement learning (deep RL) integrates the principles of reinforcement learning with deep neural networks, enabling agents to excel in diverse tasks ranging from playing board games such as Go and Chess to controlling robotic...
Machine learning (ML) has transformed the financial industry by enabling advanced applications such as credit scoring, fraud detection, and market forecasting. At the core of this transformation is deep learning (DL), a subset of ML that is robust in...
The fusion of quantum computing and artificial intelligence (AI) heralds a transformative era for Industry 4.0, offering unprecedented capabilities and challenges. This paper delves into the intricacies of quantum AI, its potential impact on Industry...
This study explores the progress of chatbot technology, focusing on the aspect of error correction to enhance these smart conversational tools. Chatbots, powered by artificial intelligence (AI), are increasingly prevalent across industries such as cu...
Background: The adoption of artificial intelligence (AI) in public administration (PA) has the potential to enhance transparency, efficiency, and responsiveness, ultimately creating greater public value. However, the integration of AI into PA faces c...
ChatGPT is an AI-powered chatbot platform that enables human users to converse with machines. It utilizes natural language processing and machine learning algorithms, transforming how people interact with AI technology. ChatGPT offers significant adv...
ChatGPT, developed by OpenAI, is a large language model (LLM) that leverages artificial intelligence (AI) and deep learning (DL) to generate human-like responses. This paper provides a broad, systematic review of ChatGPT’s applications in healt...
Deepfake technology is causing unprecedented threats to the authenticity of digital media, and demand is high for reliable digital media detection systems. This systematic review focuses on an analysis of deepfake detection methods using deep learnin...
Background: In the last decade, numerous methods have been proposed to define and detect outliers, particularly in complex environments like networks, where anomalies significantly deviate from normal patterns. Although defining a clear standard is c...
Predictive computing tools are increasingly being used and have demonstrated successfulness in providing insights that can lead to better health policy and management. However, as these technologies are still in their infancy stages, slow progress is...
In this paper, a deep learning enabled object detection model for multi-class plant disease has been proposed based on a state-of-the-art computer vision algorithm. While most existing models are limited to disease detection on a large scale, the cur...
Computer vision is a branch of computer science that studies how computers can ‘see’. It is a field that provides significant value for advancements in academia and artificial intelligence by processing images captured with a camera. In o...
Artificial intelligence (AI) has brought lots of excitement to our day-to-day lives. Some examples are spam email detection, language translation, etc. Baby monitoring devices are being used to send video data of the baby to the caregiver’s smartphon...
Large Language Models (LLMs) exhibit remarkable generative capabilities but remain vulnerable to hallucinations—outputs that are fluent yet inaccurate, ungrounded, or inconsistent with source material. To address the lack of methodologically gr...
The concept of a digital twin is intriguing as it presents an innovative approach to solving numerous real-world challenges. Initially emerging from the domains of manufacturing and engineering, digital twin research has transcended its origins and n...
Large Language Models (LLMs) are transforming cybersecurity by enabling intelligent, adaptive, and automated approaches to threat detection, vulnerability assessment, and incident response. With their advanced language understanding and contextual re...
Long Short-Term Memory (LSTM) networks have revolutionized the field of deep learning, particularly in applications that require the modeling of sequential data. Originally designed to overcome the limitations of traditional recurrent neural networks...
Recent significant advances in the healthcare industry due to artificial intelligence (AI) and machine learning (ML) have been shown to revolutionize healthcare delivery by improving efficiency, accuracy, and patient outcomes. However, these technolo...
In recent years, artificial intelligence (AI) has seen remarkable advancements, stretching the limits of what is possible and opening up new frontiers. This comparative review investigates the evolving landscape of AI advancements, providing a thorou...
Explainable Artificial Intelligence (XAI) has emerged as a crucial research area to address the interpretability challenges posed by complex machine learning models. In this survey paper, we provide a comprehensive analysis of existing approaches in...
Manuscript writing support services using AI technology have become increasingly available in recent years. In keeping with this trend, we need to sort out issues related to authorship in academic writing. Authorship is attached to the contribution o...
Fruit quality is a critical factor in the produce industry, affecting producers, distributors, consumers, and the economy. High-quality fruits are more appealing, nutritious, and safe, boosting consumer satisfaction and revenue for producers. Artific...
Besides many sectors, artificial intelligence (AI) will drive energy sector transformation, offering new approaches to optimize energy systems’ operation and reliability, ensuring techno-economic advantages. However, integrating AI into the ene...
Background/Objectives: Artificial intelligence (AI) is transforming higher education (HE), reshaping teaching, learning, and feedback processes. Feedback generated by large language models (LLMs) has shown potential for enhancing student learning out...
Data preprocessing and feature engineering play key roles in data mining initiatives, as they have a significant impact on the accuracy, reproducibility, and interpretability of analytical results. This review presents an analysis of state-of-the-art...
Digital images often become corrupted by undesirable noise during the process of acquisition, compression, storage, and transmission. Although the kinds of digital noise are varied, current denoising studies focus on denoising only a single and speci...
There is an ever-increasing application of digital platforms that utilize artificial intelligence (AI) in our daily lives. In this context, the matters of transparency and accountability remain major concerns that are yet to be effectively addressed....
In an age where artificial intelligence is reshaping the landscape of education and problem solving, our study unveils the secrets behind three digital wizards, ChatGPT-3.5, ChatGPT-4, and Google Bard, as they engage in a thrilling showdown of mathem...
Research on autonomous obstacle avoidance of drones has recently received widespread attention from researchers. Among them, an increasing number of researchers are using machine learning to train drones. These studies typically adopt supervised lear...
Weather detection systems (WDS) have an indispensable role in supporting the decisions of autonomous vehicles, especially in severe and adverse circumstances. With deep learning techniques, autonomous vehicles can effectively identify outdoor weather...
The discovery and development of new drugs is a lengthy, complex, and costly process, often requiring 10–20 years to progress from initial concept to market approval, with clinical trials representing the most resource-intensive stage. In recen...
Large language models (LLMs) have transformed Natural Language Processing (NLP) by enabling robust text generation and understanding. However, their deployment in sensitive domains like healthcare, finance, and legal services raises critical concerns...
Background/Objectives: Artificial intelligence (AI) is increasingly integrated into everyday life, including the complex and highly regulated healthcare sector. Given healthcare’s essential role in safeguarding human life and well-being, AI deploymen...
Explainable Artificial Intelligence (XAI) has become essential as machine learning systems are deployed in high-stakes domains such as security, finance, and healthcare. Traditional models often act as “black boxes”, limiting trust and ac...
This article proposes a framework for integrating ethical reasoning into AI systems through Continuous Logic Programming (CLP), emphasizing the improvement of transparency and accountability in automated decision-making. The study highlights requirem...
