The novel metaheuristic manta ray foraging optimization (MRFO) algorithm is based on the smart conduct of rays. MRFO a newly developed swarm-based approach that emulates supportive performed by rays in search food. efficiently resolves several difficulties various domains due to its ability provide an equilibrium between global and local searches during procedure, resulting nearly optimal results. Thus, researchers have variants since introduction. This paper provides in-depth examination...

In recent years, various studies have begun to use deep learning models conduct research in the field of human activity recognition (HAR). However, there has been a severe lag absolute development such since training require lot labeled data. fields as HAR, it is difficult collect data and are high costs efforts involved manual labeling. The existing methods rely heavily on collection proper labeling data, which done by administrators. This often results gathering process being slow prone...

The internet-of-Vehicle (IoV) can facilitate seamless connectivity between connected vehicles (CV), autonomous (AV), and other IoV entities. Intrusion Detection Systems (IDSs) for networks rely on machine learning (ML) to protect the in-vehicle network from cyber-attacks. Blockchain-based Federated Forests (BFFs) could be used train ML models based data entities while protecting confidentiality of reducing risks tampering with data. However, are still vulnerable evasion, poisoning...

The computing in the network (COIN) paradigm is a promising solution that leverages unused resources to perform tasks meet computation-demanding applications, such as metaverse. In this vein, we consider partial computation offloading problem metaverse for multiple subtasks COIN environment minimize energy consumption and delay while dynamically adjusting policy based on changing computational resource status. NP-hard, transform it into two subproblems: task-splitting (TSP) user side...

Current deep learning convolutional neural network (DCNN) -based hand gesture detectors with acute precision demand incredibly high-performance computing power. Although DCNN-based are capable of accurate classification, the sheer power needed for this form classification makes it very difficult to run lower computational in remote environments. Moreover, classical DCNN architectures have a fixed number input dimensions, which forces preprocessing, thus making impractical real-world...

The modern development of ultra-durable and energy-efficient IoT based communication sensors has much application in telecommunication networking sectors. Sensor calibration to reduce power usage is beneficial minimizing energy consumption as well improve the efficiency devices. Reinforcement learning (RL) been received attention from researchers now widely applied many study fields achieve intelligent automation. Though various types have used field IoT, rare researches were conducted...

Deeplearning based image classifier is getting improved day by day. The network architecture also increasing with the accuracy. But bigger size and resource intensive training makes this model impractical to deploy in IoT computational units. has limited resources reckoning power. So smaller same accuracy highly priced for application deployment. In study, convolutional deeplearning neural how pruning filters without compromising was studied. Efficient result achieved from pruned network....

Graph Neural Networks (GNNs) have emerged as a powerful framework for analyzing and extracting information from complex network data. In the realm of Digital Twin (DTN), where physical entities are mirrored in virtual environment, GNNs offer transformative approach by leveraging inherent structure relationships within digital twins. enable enhanced data representation predictive modeling. DTNs encompass several core elements that naturally conform to graph-like structure, including aspects...

The emergence of vehicle-to-cloud (V2C) technology is changing cloud computing and transportation ecosystems. V2C enables the development smart services, such as driving assistance vehicle maintenance, that transmit information to driver. Recent studies have primarily focused on services. To date, there has not been sufficient research security functions detect abnormal behaviors virtual application. If an behavior occurs in application, service only notices wrong driver, but also affects...

Cancer microarray analysis is a challenging and crucial task. Despite the vast array of methodologies that have been described, there still potential for development, especially in terms achieving more accuracy with reduced number features. The application optimization algorithms field cancer research has recently demonstrated to substantial influence. Pelican Optimization Algorithm (POA) stochastic natured motivated algorithm based on imitation foraging mechanism pelicans. Because its good...

Drowning is one of the major causes unintentional death in world. owning to this reason, there a need curb issue drowning. some systems have been developed over years, but most are not accurate detecting drowning person and do provide an effective rescue scheme prevent swimmers from The smart anti-drowning alert system which detects, rescues swimmer experiencing alerts necessary authorities. uses two sensors, pulse sensor accelerometer for detection heartbeat rate tilting pattern swimmer....

Fifth-generation (5G) core networks in network digital twins (NDTs) are complex systems with numerous components, generating considerable data. Analyzing these data can be challenging due to rare failure types, leading imbalanced classes multiclass classification. To address this problem, we propose a novel method of integrating graph Fourier transform (GFT) into message-passing neural (MPNN) designed for NDTs. This approach transforms the using GFT class imbalance, whereas MPNN extracts...

The basic premise of the Internet Things is that smart sensors collaborate directly to provide new applications.In wireless sensor networks which another foundational technology Things, interconnected intelligent sense surroundings, collect data and transmit it a sink.Since many applications in depend on battery difficult charge battery, very important establish an energy efficient path collected sink.Therefore, research improve network lifetime one challenges networks.In this paper, we...

A knowledge-based model for energy consumption management to improve the efficiency of Korean apartment complex environments is proposed. This capable controlling in accordance with characteristics residential buildings. complexes are unique and varied terms shape, type, use. Energy use data must be analyzed according building which can strongly affect pattern. Therefore, this study introduces a considering both profiles. Our proposed could used prominent method provides good reference build...

In this paper, we propose a resource allocation scheme in the frequency and time domain, to reduce interference Heterogeneous Network (HetNet) scenario for wireless sensor network. macrocell allocates band by using Soft Frequency Reuse (SFR), picocell chooses sub-bands that are not used sector, avoid interference. addition, allocate limited is difficult. Therefore, can manage cross-tier Almost Blank Subframe (ABS) domain. Simulation results show proposed improve spectrum efficiency of users....