Histopathological images are commonly used imaging modalities for breast cancer. As manual analysis of histopathological is difficult, automated tools utilizing artificial intelligence (AI) and deep learning (DL) methods should be modelled. The recent advancements in DL approaches will helpful establishing maximal image classification performance numerous application zones. This study develops an arithmetic optimization algorithm with deep-learning-based cancer (AOADL-HBCC) technique...

The rapid advancement of drone technology has expanded their applications across various sectors, necessitating robust real-time decision-making systems. Traditional algorithms often falter in dynamic and unpredictable environments. This paper introduces a fuzzy logic-based approach to enhance the capabilities autonomous drones. Utilizing Monte Carlo simulations, proposed model was evaluated through three distinct experiments involving 300, 600, 950 scenarios respectively. first experiment...

Unmanned Aerial Vehicles (UAVs), or drones, provided with camera sensors enable improved situational awareness of several emergency responses and disaster management applications, as they can function from remote complex accessing regions. The UAVs be utilized for application areas which hold sensitive data, necessitates secure processing using image encryption approaches. At the same time, embedded in latest technologies deep learning (DL) models monitoring such floods, collapsed buildings,...

Recently, the COVID-19 epidemic has had a major impact on day-to-day life of people all over globe, and it demands various kinds screening tests to detect coronavirus. Conversely, development deep learning (DL) models combined with radiological images is useful for accurate detection classification. DL are full hyperparameters, identifying optimal parameter configuration in such high dimensional space not trivial challenge. Since procedure setting hyperparameters requires expertise extensive...

Epileptic seizures are a chronic and persistent neurological illness that mainly affects the human brain. Electroencephalogram (EEG) is considered an effective tool among neurologists to detect various brain disorders, including epilepsy, owing its advantages, such as low cost, simplicity, availability. In order reduce severity of epileptic seizures, it necessary design techniques identify disease at earlier stage. Since traditional way diagnosing laborious time-consuming, automated tools...

Cyberbullying (CB) is a distressing online behavior that disturbs mental health significantly. Earlier studies have employed statistical and Machine Learning (ML) techniques for CB detection. With this motivation, the current paper presents an Optimal Deep Learning-based Detection Classification (ODL-CDC) technique detection in social networks. The proposed ODL-CDC involves different processes such as pre-processing, prediction, hyperparameter optimization. In addition, GloVe approach...

In recent times, Industrial Internet of Things (IIoT) experiences a high risk cyber attacks which needs to be resolved. Blockchain technology can incorporated into IIoT system help the entrepreneurs realize Industry 4.0 by overcoming such attacks. Although blockchain-based network renders significant support and meet service requirements next generation network, performance arrived at, in existing studies still improvement. this scenario, current research paper develops new...

In the present era, cancer is leading cause of demise in both men and women worldwide, with low survival rates due to inefficient diagnostic techniques. Recently, researchers have been devising methods improve prediction performance. medical image processing, enhancement can further This study aimed lung quality by utilizing employing various methods, such as adjustment, gamma correction, contrast stretching, thresholding, histogram equalization methods. We extracted gray-level co-occurrence...

Recently, Telehealth connects patients to vital healthcare services via remote monitoring, wireless communications, videoconferencing, and electronic consults. By increasing access specialists physicians, telehealth assists in ensuring receive the proper care at right time place. Teleophthalmology is a study of telemedicine that provides for eye using digital medical equipment telecommunication technologies. Multimedia computing with Explainable Artificial Intelligence (XAI) has potential...

Remote sensing image (RSI) scene classification has become a hot research topic due to its applicability in different domains such as object recognition, land use classification, retrieval, and surveillance. During RSI process, class label will be allocated every based on the semantic details, which is significant real-time applications mineral exploration, forestry, vegetation, weather, oceanography. Deep learning (DL) approaches, particularly convolutional neural network (CNN), have shown...

Data mining in the educational field can be used to optimize teaching and learning performance among students. The recently developed machine (ML) deep (DL) approaches utilized mine data effectively. This study proposes an Improved Sailfish Optimizer-based Feature Selection with Optimal Stacked Sparse Autoencoder (ISOFS-OSSAE) for pattern recognition sector. proposed ISOFS-OSSAE model aims derive decisions based on feature selection classification process. Moreover, involves design of ISOFS...

Energy is a major driver of human activity. Demand response the utmost importance to maintain efficient and reliable operation smart grid systems. The short-term load forecasting (STLF) method particularly significant for electric fields in trade energy. This model has several applications everyday operations utilities, namely switching, energy-generation planning, contract evaluation, energy purchasing, infrastructure maintenance. A considerable number STLF algorithms have introduced...

Cloud computing (CC) refers to an Internet-based technology in which shared resources, such as storage, software, information, and platform, are offered users on demand. CC is a through virtualized dynamically scalable resources presented the Internet. Security highly significant this on-demand CC. Therefore, paper presents improved metaheuristics with fuzzy logic-based intrusion detection system for cloud security (IMFL-IDSCS) technique. The IMFL-IDSCS technique can identify intrusions...

Brain Computer Interface (BCI) technology commonly used to enable communication for the person with movement disability. It allows communicate and control assistive robots by use of electroencephalogram (EEG) or other brain signals. Though several approaches have been available in literature learning EEG signal feature, deep (DL) models need further explore generating novel representation features accomplish enhanced outcomes MI classification. With this motivation, study designs an...

As cyberattacks develop in volume and complexity, machine learning (ML) was extremely implemented for managing several cybersecurity attacks malicious performance. The cyber-physical systems (CPSs) combined the calculation with physical procedures. An embedded computer network monitor control procedure, commonly feedback loops whereas procedures affect calculations conversely, at same time, ML approaches were vulnerable to data pollution attacks. Improving security attaining robustness of...

Purification of polluted water and return back to the agriculture field is wastewater treatment for plants. Contaminated causes illness health emergencies public. Also, risk due release toxic contaminants brings problem all living beings. At present, sensors are used in waste transfer data via internet things (IoT). Prediction quality content which presence total nitrogen (T-N) phosphorous (T-P) elements, chemical oxygen demand (COD), biochemical (BOD), suspended solids (TSS) associated with...

Sign language includes the motion of arms and hands to communicate with people hearing disabilities. Several models have been available in literature for sign detection classification enhanced outcomes. But latest advancements computer vision enable us perform signs/gesture recognition using deep neural networks. This paper introduces an Arabic Language Gesture Classification Deer Hunting Optimization Machine Learning (ASLGC-DHOML) model. The presented ASLGC-DHOML technique mainly...

Oral cancer is considered one of the most common types in several counties. Earlier-stage identification essential for better prognosis, treatment, and survival. To enhance precision medicine, Internet Medical Things (IoMT) deep learning (DL) models can be developed automated oral classification to improve detection rate decrease cancer-specific mortality. This article focuses on design an optimal Inception-Deep Convolution Neural Network Potentially Malignant Disorder Detection...

The Internet of Things (IoT) has gained more popularity in research because its large-scale challenges and implementation. But security was the main concern when witnessing fast development applications size. It a dreary task to independently set systems every IoT gadget upgrade them according newer threats. Additionally, machine learning (ML) techniques optimally use colossal volume data generated by devices. Deep Learning (DL) related were modelled for attack detection IoT. current address...

The real world is bounded by people, hospitals, industries, buildings, businesses, vehicles, cognitive cities, and billions of devices that offer various services interact with the world. Recent technologies, including AR, VR, XR, digital twin concept, provide advanced solutions to create a new virtual Due ongoing development information communication technologies broadcast channels, data security has become major concern. Blockchain (BC) technology an open, decentralized, transparent...