A5083433378- Indoor and Outdoor Localization Technologies
- Quality and Safety in Healthcare
- Image and Signal Denoising Methods
- Advanced Image Processing Techniques
- Currency Recognition and Detection
- Fault Detection and Control Systems
- Domain Adaptation and Few-Shot Learning
- Data Quality and Management
- Autism Spectrum Disorder Research
- Multimedia Learning Systems
- Machine Fault Diagnosis Techniques
- Anomaly Detection Techniques and Applications
- Industrial Vision Systems and Defect Detection
- Robotics and Sensor-Based Localization
- Forecasting Techniques and Applications
- Underwater Vehicles and Communication Systems
- Advanced Image Fusion Techniques
- Advanced Graph Neural Networks
- Face recognition and analysis
- Data Mining and Machine Learning Applications
- Data Mining Algorithms and Applications
- Stock Market Forecasting Methods
- Assistive Technology in Communication and Mobility
Ollscoil na Gaillimhe – University of Galway
2022-2024
Institut Teknologi dan Sains Mandala
2024
Binus University
2023
Jeonbuk National University
2015-2017
The proliferation of sensing technologies such as sensors has resulted in vast amounts time-series data being produced by machines industrial plants and factories. There is much information available that can be used to predict machine breakdown degradation a given factory. downtime equipment accounts for heavy losses revenue reduced making accurate failure predictions using the sensor data. Internet Things (IoT) have made it possible collect real time. We found hybrid modelling result...
Abstract Estimating the remaining useful life (RUL) of critical industrial assets is crucial importance for optimizing maintenance strategies, enabling proactive planning repair tasks, enhanced reliability, and reduced downtime in prognostic health management (PHM). Deep learning-based data-driven approaches have made RUL prediction a lot better, but traditional methods often do not look at similarities differences data, which lowers accuracy estimates. Previous attempts to use Long...
The integration of heterogeneous and unstructured data in Industry 4.0, poses a significant challenge, particularly with advanced manufacturing techniques. To address this issue, Knowledge Graphs (KGs) have emerged as pivotal technology, yet their deployment often encounters the problem incompletion due to diversity diverse storage formats. This study tackles challenge KG completion by applying evaluating state-of-the-art embedding models-ComplEx, DistMult, TransE, ConvKB, ConvE-within...
In this paper, an indoor localization method based on Kalman filtered RSSI is presented. The communications environment however rather harsh to the mobiles since there a substantial number of objects distorting signals; fading and interference are main sources distortion. filter adopted signals trilateration applied obtain robust accurate coordinates mobile station. From experiments using WiFi stations, we have found that proposed algorithm can provide higher accuracy with relatively lower...
Cryptocurrency has become an increasingly popular digital asset in recent years. However, cryptocurrency prices are highly volatile and difficult to predict due being influenced by many factors such as market sentiment, regulations, technological adoption. This study aims analyze the performance of several machine learning algorithms accurately predicting prices. We evaluated four algorithms: Linear Regression, Random Forest, Support Vector Machine (SVM), Long Short-Term Memory (LSTM) using...
Age estimation from facial images is a challenging topic in computer vision since it can automatically label the human face with an exact age according to various physical or biological characteristics, such as structure, spots, and wrinkles. Additionally, has substantial applications many fields, including healthcare, security, entertainment, education. There are lot of techniques estimate age, but most popular one convolutional neural network (CNN), which offers high accuracy needs...
Image restoration and reconstruction from blurry noisy images have proved to be challenging problem. Noise removal plays any important role in preserving the meaningful useful information images. Our paper is based on a denoising technique known as total variation (TV). Over years, high quality videos become trend. However, noise has remained an integral part videos. Many techniques been developed over time remove Linear filters, Non-Linear median filters their modifications, great success...