Aim: Scope of this work aims to explore the effectiveness of AI-powered outbound dialer campaigns with legacy outbound dialer campaigns by evaluating their technological capabilities, operational efficiencies, compliance features, customer experience impact, cost-effectiveness, a...
Open access
Research Article10.9734/ajrcos/2025/v18i3580
Various critical issues in liver diseases include cirrhosis, hepatitis, and liver cancer, which can be fatal. They indeed require early diagnosis with appropriate diagnosis of the disease. The different conventional diagnostic methods generally can't identify these diseases durin...
Open access
Research Article10.9734/ajrcos/2025/v18i3574
Adaptive search algorithms have emerged as pivotal tools for addressing complex, high-dimensional, and nonlinear challenges across various domains. This paper provides a detailed review of adaptive search techniques, including evolutionary algorithms, swarm intelligence methods,...
Open access
Research Article10.9734/ajrcos/2025/v18i3575
The article addresses existing methods for enhancing the performance of microservice architectures under high-load conditions, where stability and scalability are required to adapt to changing demands. The objective of the study is to systematize existing optimization methods. Th...
Open access
Research Article10.9734/ajrcos/2025/v18i3577
The greatest technical achievement of the twenty-first century is machine learning (ML). The application of machine learning to detect cybersecurity vulnerabilities is a significant advancement in information security. A void exists in the field since the widespread application o...
Open access
Research Article10.9734/ajrcos/2025/v18i2572
Recent years have seen the proposal of numerous routing algorithms for potential use in a variety of application areas. In many network types, such as Wireless Sensor Networks (WSNs), Mobile Ad Hoc Networks (MANETs), and other dynamic contexts, routing is a crucial difficulty. By...
Open access
Research Article10.9734/ajrcos/2025/v18i3573
Overfitting remains a significant challenge in training neural networks, often leading to poor generalization on unseen data. Dropout has emerged as a powerful regularization technique to mitigate overfitting by randomly deactivating neurons during training, thereby preventing co...
Open access
Research Article10.9734/ajrcos/2025/v18i2569
Early detection of neurodegenerative diseases like Alzheimer’s and Parkinson’s is crucial for improving patient care and enabling timely interventions. Artificial intelligence (AI) offers innovative approaches to analyzing complex medical datasets, revolutionizing the detection o...
Open access
Research Article10.9734/ajrcos/2025/v18i2570
The increasing reliance on Internet-based services has rendered secure and efficient network traffic classification critical. Conventional methods for categorising traffic, such as port and payload methods, often struggle with the challenges posed by encrypted traffic. Deep learn...
Open access
Research Article10.9734/ajrcos/2025/v18i2571
The tutorial analyses how and in what ways the algorithms are used and can be employed in different fields and in the scientific context. This paper revisits the centrality measures; degree, betweenness, closeness and eigenvector centrality and how they are used to study complex...
Open access
Research Article10.9734/ajrcos/2025/v18i2568
Diabetic retinopathy, a condition resulting from prolonged high blood sugar levels that damage the retina, can cause vision impairment and, if untreated, lead to blindness. With advances in medical imaging and the availability of fundus image collections such as Madrid Messidor a...
Open access
Research Article10.9734/ajrcos/2025/v18i2566
The advancement of information technology is rapidly changing the face of cyber security and this makes it more important with the increasing trend of sophistication of cyber threats in the society. The authors in this research aim at analyze how AI and ML can improve cybersecuri...
Open access
Research Article10.9734/ajrcos/2025/v18i2567
Aims: The purpose of this study is to classify invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC) of breast cancer using the artificial neural networks recurrent algorithm. the use of artificial neural networks Recurrent algorithms can improve the accuracy of br...
Open access
Research Article10.9734/ajrcos/2025/v18i2563
This study investigates the effectiveness of collaborative digital solutions in addressing cybersecurity governance gaps within the educational sector, focusing on resource constraints, awareness deficits, and regulatory compliance challenges. Data from the National Institute of...
Open access
Research Article10.9734/ajrcos/2025/v18i2564
The significance of image recognition technology is highlighted by its wide applications in fields such as security, medical image analysis, and data analysis. Its growing popularity reflects advancements in research. Traditional machine learning methods have markedly improved fe...
Open access
Research Article10.9734/ajrcos/2025/v18i2565