This research aims to analyze the continuous structure involved in developing Artificial Intelligence (AI)-based healthcare systems ensure sustainable outcomes. A comparison is made between organizational objectives system determine proper use of AI architectural design. The study will delve into results obtained from using design and highlight activities found perform tasks. provide insights potential improving sector. this be helpful for organizations individuals interested incorporating...

Abstract The advancement of information technology, the Internet Things (IoT), and several miniaturize equipment's enhances healthcare field that provides real‐time patient monitoring, which helps to provide medication anywhere anytime. However, accurate detection is still a challenging task for an effective classification model introduced in this research. proposed method Enhanced Hunt optimization based Deep convolutional neural network (Enhanced based‐Deep CNN), algorithm (EHOA) developed...

Brain tumours are regarded as a fatal condition that impacts the lives of so many people worldwide. The kind, location, and size brain tumour all affect how it will be treated. Hence, an automated diagnosis is needed for early detection. Convolutional neural networks (CNNs) have become increasingly desired in recent times tasks like these. In this work, we performed multi-class classification into different types over MRI scans. For these several convolutional used comparative analysis made...

Abstract The attack named Distributed Denial of Service (DDoS) that takes place in the large blockchain network requires an efficient and robust detection prevention mechanism for authenticated access. Blockchain is a distributed which attacker tries to hack by utilizing all resources with application enormous requests. Several methods like Rival Technique, filter modular approach so on, were developed detect prevent DDoS blockchain; still, accuracy challenging task. Hence, this research...

Early identification of diabetes is vital since it's an incurable condition with no complete cure. We used data mining and machine learning strategies in our investigation to anticipate diabetes. 768 individuals their relevant attributes are the focus hour. Few methods have been applied dataset for goal forecasting occurrence The implemented algorithms' consistency harshness investigated using that focused on correlating accuracy F-1 rankings. Comparison between algorithms done increase...

The utilization of Artificial Intelligence (AI)-enabled software and hardware is expected to enhance the effectiveness monetary exchanges, which main objective this research. Since transaction costs are based on actual amount being transferred, customers feel more at ease making purchases using approach. This work aims investigate role financial systems in effective corporate administration, with a particular emphasis gateways as key components these systems. study investigates factors...

Data anomalies are found using anomaly detection. Generative adversarial networks (GANs) can produce synthetic data and learn complex patterns. Temporal dependencies relevant features needed to identify timeseries anomalies. A GAN is trained detect in data. The model performs better with Traditional ML models struggle the difficulties of identification time-series due issues such as dealing high dimensionality, capturing temporal correlations, detecting infrequent events skewed class...

Software-defined networking (SDN) has significantly transformed the field of network management through consolidation control and provision enhanced adaptability. However, this paradigm shift concurrently presented novel security concerns. The preservation service path integrity holds significant importance within SDN environments due to potential for malevolent entities exploit flows, resulting in a range breaches. This research paper introduces model called "EnsureS", which aims enhance by...

Abstract Detection of cyber‐threats in the smart grid Supervisory Control and Data Acquisition (SCADA) is still remains one complex essential processes need to be highly concentrated present times. Typically, SCADA more prone security issues due their environmental problems vulnerabilities. Therefore, proposed work intends design a new detection approach by integrating optimization classification models for security. In this framework, min‐max normalization performed at first noise removal...

With many gaps and shortcomings in the field of IoT security, no matter how simple you think it is on your side what goes inside an intrusion detection system technique to detect attacks. This study explores current state IDS IoT. The most important points vulnerability are identified, we examine ways address them immediately. One key finding research that interoperability problems between differing devices platforms loom as two big roadblocks. Besides, lack standardized evaluation standards...

Many industries have serious concerns about the secure transmission of sensitive data, and use blockchain technology, steganography, optimization algorithms has emerged as a potent remedy. Steganography can hide data increase effectiveness process, while technology offers transparent platform for storage transfer. The employment these technologies in tandem to offer reliable solution transfer is provided this paper. We also go over strategy's possible advantages difficulties suggestions...

In order to improve the secure transfer of sensitive data, this paper investigates integration blockchain, steganography, and optimization algorithms. By obscuring data within files, boosting anonymity in blockchain transactions, enabling watermarking for evidence ownership, steganography enhances blockchain. concealing access credentials, it protects document exchange guarantees integrity IoT. Steganography work together security privacy. A strong solution is put forth by combining these...

Worldwide Interoperability for Microwave Access applications and QoS specifications are based upon class schemes. These service classes effect to user fairness system utilization. Improved MAX C/I algorithm considers waiting time channel interference ratio but not scheduling schemes, after including this neglecting condition solves the problem of long distance priorities. RR scheduled instructions execution where queue priorities users set. But gain criteria, now mDmT resolves those...

Abstract The Internet of Vehicles (IoV) is an element the global connectivity infrastructure Connected vehicles are beneficial to health their users in a significant way. However, several drawbacks have been identified, creating potential for compromised devices. Moreover, high mobility results energy consumption, which reduces network's overall performance. Efficient Privacy-preserving Lightweight-cryptography Cluster-based (EPLC-IoV) model that has proposed divided into five distinct...

Cloud computing has become a revolution of modern computer paradigms, offering adaptable resources to the utmost. But thread operations inside cloud environments still fall under critical challenge for efficient processing and resource utilization. Integration blockchain technology would be new, transformative opportunity optimizing threads. Straddling realms infrastructure, this paper discusses threads examines how distributing program can lead better computational efficiency using...