Consistent Academic Support
Science Net ensures that research activities continue without interruption in the current global situation. Participants can engage through digital and hybrid conference formats.
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Conference Program
Session Tracks
Aligned with
UN Sustainable Development Goals
This conference contributes to global sustainability by aligning its research discussions and academic sessions with key United Nations Sustainable Development Goals. It fosters knowledge exchange, innovation, and collaborative engagement.
Why it matters
SDG 8 — Decent Work and Economic Growth
SDG 9 — Industry, Innovation and Infrastructure
SDG 11 — Sustainable Cities and Communities
SDG 12 — Responsible Consumption and Production
Explore
All Session Tracks
Track 01
Advancements in Predictive Modeling Techniques
This track focuses on the latest methodologies in predictive modeling, emphasizing their applications in various engineering domains. Participants will explore both supervised and unsupervised learning techniques that enhance predictive accuracy.
Track 02
Deep Learning Applications in Signal Processing
This session will delve into the integration of deep learning frameworks in signal processing tasks. Attendees will discuss innovative approaches that leverage neural networks for improved signal analysis and interpretation.
Track 03
Anomaly Detection in Sensor Data
This track addresses the challenges and solutions related to anomaly detection in sensor data streams. Participants will share insights on algorithms and techniques that enhance the reliability of data-driven decision-making.
Track 04
Feature Extraction Methods for Enhanced Data Analysis
This session will cover advanced feature extraction techniques that facilitate better data representation and analysis. The focus will be on methods that improve model performance in engineering applications.
Track 05
Time Series Processing in Engineering Applications
This track explores methodologies for effective time series processing, particularly in engineering contexts. Participants will discuss challenges and solutions related to forecasting and trend analysis.
Track 06
Predictive Maintenance Strategies Using Data Science
This session will focus on the integration of data science techniques in predictive maintenance strategies. Attendees will explore case studies that demonstrate the impact of data-driven insights on operational efficiency.
Track 07
Real-Time Analytics for Industrial IoT
This track examines the role of real-time analytics in the context of Industrial Internet of Things (IIoT). Participants will discuss frameworks and tools that enable immediate data processing and actionable insights.
Track 08
Signal Filtering Techniques and Applications
This session will explore various signal filtering techniques and their practical applications in engineering. Participants will discuss the effectiveness of different filtering methods in enhancing signal quality.
Track 09
Fast Fourier Transform (FFT) Analysis in Data Science
This track focuses on the application of Fast Fourier Transform (FFT) in data science for signal analysis. Participants will explore its utility in frequency domain analysis and its implications for engineering solutions.
Track 10
Adaptive Learning Approaches in Data Science
This session will delve into adaptive learning techniques that allow models to evolve with changing data patterns. Participants will discuss the implications of these approaches for real-world engineering challenges.
Track 11
Data Fusion Techniques for Enhanced Decision Making
This track addresses the integration of multiple data sources through data fusion techniques. Participants will explore methodologies that improve decision-making processes in engineering applications.