19 hasil untuk "Thompson Stephan"
Menampilkan 1–19 · 2,38 detik · RSS
-
Artikel Jurnal
A penalty-embedded genetic algorithm for interpretable clinical feature selection in heart disease prediction
Heart disease decision support often requires identifying a small set of routine clinical tests that preserves reliable multi-class predictive performance while reducing diagnostic burden. However, many metaheuristic wrapper studies emphasize accuracy and rely on implicit or post hoc size control…
-
Artikel Jurnal
Interpretable wrapper-based machine learning framework for predicting patellofemoral pain syndrome using minimal clinical tests
Abstract Clinical screening for patellofemoral pain syndrome (PFPS), a leading cause of anterior knee pain in athletes and physically active populations, often involves numerous physical tests. Such lengthy examinations are further compounded when considering the regional interdependence model…
-
Artikel Jurnal
A Comprehensive Study of Grey Wolf Optimizer Variants for Optimizing Feature Selection in High-Dimensional Data
Metaheuristic algorithms, notably the Grey Wolf Optimizer (GWO), are widely used for wrapper-based feature selection due to their superior ability to balance exploration and exploitation. We conduct a comparative evaluation of the original GWO and eight established variants on ten benchmark…
-
Artikel Jurnal
Intelligent techniques for predictive analytics in Agile software development
Abstract The increasing complexity of software development projects necessitates advanced tools and methodologies for effective project management. Predictive analytics, specifically the estimation of issue resolution times, plays a crucial role in enhancing decision-making processes, resource…
-
Artikel Jurnal
Energy-efficient blockchain implementation for Cognitive Wireless Communication Networks (CWCNs)
Considering the computation resources available with sensor devices and the value and validity of Cognitive Wireless Communication Network (CWCN), traditional blockchain is not feasible for CWCN. Further, considering the security and privacy for CWCN that can directly impact human life (as in the…
-
Artikel Jurnal
Capturing-the-Invisible (CTI): Behavior-Based Attacks Recognition in IoT-Oriented Industrial Control Systems
Industrial Control Systems monitor, automate, and operate complex infrastructure and processes that integrate into critical industrial sectors that affect our daily lives. With the advent of networking and automation, these systems have moved from being dedicated and independent to centralized…
-
Artikel Jurnal
Efficient person re-identification via progressive filter pruning and body part-aware feature learning
Abstract Person re-identification (Re-ID) is a critical task in modern surveillance, enabling the tracking of individuals across multiple camera views despite variations in appearance, pose, and background. As public safety demands grow, Re-ID systems must operate efficiently in real-time…
-
Artikel Jurnal
SPA-IoT with MCSV-CNN: a novel IoT-enabled method for robust pre-ictal seizure prediction
Abstract This paper introduces a new approach to real-time epileptic seizure prediction using a lightweight Convolutional Neural Network (CNN) architecture and multiresolution feature extraction from electroencephalogram (EEG) recordings. Multiresolution Critical Spectral Verge CNN (MCSV-CNN), the…
-
Artikel Jurnal
An edge-enabled multimodal Smart Home Energy Management System using deep learning
Abstract The rapid proliferation of Internet of Things (IoT) technologies has significantly transformed smart home environments. Heterogeneity of various IoT applications generally leads to interoperability requirements that needs to be fulfilled along with ensuring federated device configuration…
-
Artikel Jurnal
Federated learning-driven IoT system for automated freshness monitoring in resource-constrained vending carts
Abstract Street vendors in developing regions often lack access to portable and affordable cold storage, leading to accelerated food spoilage, financial losses, and health risks. Traditional refrigeration solutions are bulky and costly, while manual freshness assessment is error-prone. This study…
-
Artikel Jurnal
Detecting COVID-19 From Lung Computed Tomography Images: A Swarm Optimized Artificial Neural Network Approach
COVID-19 has affected many people across the globe. Though vaccines are available now, early detection of the disease plays a vital role in the better management of COVID-19 patients. An Artificial Neural Network (ANN) powered Computer Aided Diagnosis (CAD) system can automate the detection…
-
Artikel Jurnal
GAN-TL domain-adaptive augmentation for enhanced transfer learning
Abstract Transfer learning offers a practical solution for label-scarce target domains, but its effectiveness diminishes when source and target data follow different distributions. To address this challenge, we present GAN-TL, a GAN-augmented transfer learning framework that generates target-style…
-
Artikel Jurnal
ProWaste for proactive urban waste management using IoT and machine learning
Abstract Urban waste-collection centres (WCCs) routinely overflow because maintenance routes are scheduled reactively rather than on data-driven forecasts. Overspill, odour, and leachate therefore threaten public health and sustainability targets in rapidly growing smart cities. We introduce…
-
Artikel Jurnal Teks lengkap
A Novel Approach for Multichannel Epileptic Seizure Classification Based on Internet of Things Framework Using Critical Spectral Verge Feature Derived from Flower Pollination Algorithm
A novel approach for multichannel epilepsy seizure classification which will help to automatically locate seizure activity present in the focal brain region was proposed. This paper suggested an Internet of Things (IoT) framework based on a smart phone by utilizing a novel feature termed…
-
Artikel Jurnal
An Investigative Study on the Effects of Pedagogical Agents on Intrinsic, Extraneous and Germane Cognitive Load: Experimental Findings With Dyscalculia and Non-Dyscalculia Learners
Several studies have warranted the need to explore the relationship between pedagogical agents in the learning environment and the cognitive load on the learners, specifically, to study the influence on learner populations with different learning and motivation needs. The present work investigates…
-
Artikel Jurnal
EEG-based neurodegenerative disease diagnosis: comparative analysis of conventional methods and deep learning models
Abstract In the context of lifestyle changes, stress and other environmental factors have resulted in the sudden hike in dementia globally. This necessitates investigations with respect to every horizon of the due cause for it; further on, the diagnosis and treatments can be advanced with the aid…
-
Artikel Jurnal
Quantum-enhanced deep learning models for automated defect detection in materials
The quality of raw materials is fundamental to the reliability and overall performance of final products, serving as the cornerstone of modern manufacturing standards. While traditional inspection methods can be effective, they are frequently time-consuming, labor-intensive, and unsuitable for…
-
Artikel Jurnal
iWorksafe: Towards Healthy Workplaces During COVID-19 With an Intelligent Phealth App for Industrial Settings
The recent outbreak of the novel Coronavirus Disease (COVID-19) has given rise to diverse health issues due to its high transmission rate and limited treatment options. Almost the whole world, at some point of time, was placed in lock-down in an attempt to stop the spread of the virus, with…