This paper presents a comprehensive study of Convolutional Neural Networks (CNN) and transfer learning in the context medical imaging. Medical imaging plays critical role diagnosis treatment diseases, CNN-based models have demonstrated significant improvements image analysis classification tasks. Transfer learning, which involves reusing pre-trained CNN models, has also shown promise addressing challenges related to small datasets limited computational resources. reviews advantages imaging,...

The ability to predict the radioactive soil radon gas concentration is important for human beings because it serves as a precursor earthquakes. Several studies have been conducted across globe confirm correlation of emission dynamics and earthquakes, concluded that witness anomalous behaviour before occurrences several This behavior can help construct better prediction model earthquake forecasting. paper aims at employing different ensemble individual machine learning methods on real time...

Decision-making medical systems (DMS) refer to the design of decision techniques in healthcare sector. They involve a procedure employing ideas and decisions related certain processes such as data acquisition, processing, judgment, conclusion. Pancreatic cancer is lethal type cancer, its prediction ineffective with current techniques. Automated detection classification pancreatic tumors can be provided by computer-aided diagnosis (CAD) model using radiological images computed tomography (CT)...

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...

Wearable devices such as smartwatches, wristbands, and GPS shoes are commonly employed for fitness wellness they enable people to observe their day-to-day health status. These gadgets encompass sensors accumulate data related user activities. Clinical act graph come under the class of wearables worn on wrist compute sleep parameters by storing movements. Sleep is very important a healthy lifestyle. Inadequate can obstruct physical, emotional, mental health, could result in several illnesses...

In real‐time, visually impaired persons face challenging issues in identifying and avoiding obstacles their path, making it difficult to move around freely confidently. Object detection technology benefits contains the procedure of determining several individual objects from image recognizing place with bounding boxes class labels. Both exploit typical machine learning (ML) approaches utilize deep (DL) models execute object methods. Recently, researchers have leveraged DL techniques such as...

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...

The recent combination of ambient backscatter communication (ABC) with non-orthogonal multiple access (NOMA) has shown great potential for connecting large-scale Internet Things (IoT) in future unmanned aerial vehicle (UAV) networks. basic idea ABC is to provide battery-free transmission by harvesting the energy existing RF signals WiFi, TV towers, and cellular base stations/UAV. uses smart sensor tags modulate reflect data among wireless devices. On other side, NOMA makes possible more than...

The seamless operation of interconnected smart devices in wireless sensor networks (WSN) and the Internet Things (IoT) needs continuously accessible end-to-end routes. However, node (SN) relies on a limited power source tends to cause disconnection multi-hop routes because shortage WSN, eventually leading inefficiency total IoT network. Furthermore, density available SNs affects existence feasible level path multiplicity WSN. Thus, an effective routing model is predictable extend lifetime...

The increasing demands of several emergent services brought new communication problems to vehicular networks (VNs). It is predicted that the transmission system assimilated with unmanned aerial vehicles (UAVs) fulfills requirement next-generation network. Because its higher flexible mobility, UAV-aided network brings transformative and far-reaching benefits extremely high data rates; considerably improved security reliability; massive hyper-fast wireless access; much greener, smarter, longer...

Barnacles Mating Optimizer (BMO) is a new metaheuristic algorithm that suffers from slow convergence and poor efficiency due to its limited capability in exploiting the search space exploring promising regions. Addressing these shortcomings, this paper introduces Elitist (eBMO). Unlike BMO, eBMO exploits elite exponential probability (Pelite) decide whether intensify process via swap operator or diversify by randomly Furthermore, uses Chebyshev map instead of random numbers generate quality...

Wireless sensor networks (WSNs) are becoming a significant technology for ubiquitous living and continue to be involved in active research because of their varied applications. Energy awareness will critical design problem WSNs. Clustering is widespread energy-efficient method grants several benefits such as scalability, energy efficiency, less delay, lifetime, but it results hotspot issues. To solve this, unequal clustering (UC) has been presented. In UC, the size cluster differs with...

In recent times, wireless sensor network (WSN) finds their suitability in several application areas, ranging from military to commercial ones. Since nodes WSN are placed arbitrarily the target field, node localization (NL) becomes essential where positioning of can be determined by aid anchor nodes. The goal any NL scheme is improve accuracy and reduce error rate. With this motivation, study focuses on design Intelligent Aquila Optimization Algorithm Based Node Localization Scheme...

Currently, there are many limitations to classify images of small objects. In addition, such as error detection due external factors, and is also a disadvantage that it difficult accurately distinguish between various This paper uses convolutional neural network (CNN) algorithm recognize object very moths obtain precise data images. A convolution used for image classification, the classified transformed into learn topological structure image. To improve accuracy classification reduce loss...

Unmanned aerial vehicles (UAVs) are assumed to be a promising model of automatic emergency tasks in dynamic marine ecosystems. But, the real-time communication efficacy betwixt UAVs and base platforms is developing serious challenge. The compact-sized powerful flying robots can wirelessly controlled accomplish end with without human involvement. still face severe challenges that limit dream completely autonomous unmanned machines. main difficulties contain path planning hindrance avoidance...

Prediction of the maintainability classes in object-oriented systems is a significant factor for software success, however it challenging task to achieve. To date, several machine learning models have been applied with variable results and no clear indication which techniques are more appropriate. With goal achieving consistent results, this paper presents first set an extensive empirical study designed evaluate capability bagging increase accuracy prediction over individual models. The...

While prior object-oriented software maintainability literature acknowledges the role of machine learning techniques as valuable predictors potential change, most suitable technique that achieves consistently high accuracy remains undetermined. With objective obtaining more consistent results, an ensemble is investigated to advance performance individual models and increase their in predicting system. This paper describes research plan for using techniques. First, we present a brief overview...

Social media is a platform in which user can create, share and exchange the knowledge/information. marketing to identify different consumer's demands engages them create resources. The popular social platforms are Microsoft, Snapchat, Amazon, Flipkart, Google, eBay, Instagram, Facebook, Pin interest, Twitter. main aim of deals with various business partners build good relationship millions customers by satisfying their needs. Disruptive technology replacing old approaches new...

Various prediction models have been proposed by researchers to predict the change-proneness of classes based on source code metrics. However, some these suffer from low accuracy because datasets exhibit high dimensionality or imbalanced classes. Recent studies suggest that using ensembles integrate several models, select features, perform sampling has potential resolve issues in and improve accuracy. This study aims empirically evaluate effectiveness ensemble feature selection, techniques...

In present digital era, data science techniques exploit artificial intelligence (AI) who start and run small medium-sized enterprises (SMEs) to have an impact develop their businesses. Data integrates the conventions of econometrics with technological elements science. It make use machine learning (ML), predictive prescriptive analytics effectively understand financial solve related problems. Smart technologies for SMEs enable allows firm get smarter processes offers efficient operations. At...

Next-generation Internet-of-Things applications pose challenges for sixth-generation (6G) mobile networks, involving large bandwidth, increased network capabilities, and remarkably low latency. The possibility of using ultra-dense connectivity to address the existing problem was previously well-acknowledged. Therefore, placing base stations (BSs) is economically challenging. Drone-based can efficiently requirements while accelerating growth expansion. Due their versatility, they also manage...