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Topic Review
Large-Scale Unstructured Unsteady Flow
Animation visualization is one of the primary methods for analyzing unsteady flow fields. Loading and rendering individual time steps sequentially can result in substantial frame delay, whereas loading and rendering all time steps simultaneously can result in excessive memory usage.
  • 111
  • 28 Nov 2023
Topic Review
Laser Cutting Path Problem
Efficiently cutting smaller two-dimensional parts from a larger surface area is a recurring challenge in many manufacturing environments. This point falls under the cut-and-pack (C&P) problems. This research specifically focused on a specialization of the cut path determination (CPD) known as the laser cutting path planning (LCPP) problem.
  • 119
  • 24 Nov 2023
Topic Review
Noise Suppression by Artificial Intelligence
Noise suppression algorithms have been used in various tasks such as computer vision, industrial inspection, and video surveillance, among others. Noise suppression has become a dynamic field within the domain of image processing. This is due to the fact that as technological advances emerge, a greater understanding of the scene in which a vision system is interacting is required.
  • 171
  • 23 Nov 2023
Topic Review
Vehicular Ad Hoc Network in a Parking Lot
Vehicular ad hoc networks (VANETs) are provided as an important component of Intelligent Transportation Systems (ITS) especially for enhancing traffic safety. The primary goal of VANETs is to improve the safety of drivers and passengers by facilitating the exchange of information between vehicles.
  • 138
  • 22 Nov 2023
Topic Review
Predictability Measures
The task of forecasting is a crucial topic with wide-range applications and significance in various fields. In fact, forecasting provides valuable insights into the future, helping individuals, organizations, and societies plan and adapt in a dynamic and uncertain world. Time series and network link are among the most significant and extensively investigated objects that have been the focus of forecasting efforts.
  • 155
  • 22 Nov 2023
Topic Review
Cognitive Personalization of Microtask Design
The study of data quality in crowdsourcing campaigns is a prominent research topic, given the diverse range of participants involved. A potential solution to enhancing data quality processes in crowdsourcing is cognitive personalization, which involves appropriately adapting or assigning tasks based on a crowd worker’s cognitive profile. There are two common methods for assessing a crowd worker’s cognitive profile: administering online cognitive tests, and inferring behavior from task fingerprinting based on user interaction log events. 
  • 124
  • 22 Nov 2023
Topic Review
GAN-Based Applications in Parkinson’s Disease Diagnosis and Treatment
Data scarcity in the healthcare domain is a major drawback for most state-of-the-art technologies engaging artificial intelligence. The unavailability of quality data due to both the difficulty to gather and label them as well as due to their sensitive nature create a breeding ground for data augmentation solutions. Parkinson’s Disease (PD) which can have a wide range of symptoms including motor impairments consists of a very challenging case for quality data acquisition. Generative Adversarial Networks (GANs) can help alleviate such data availability issues.
  • 172
  • 22 Nov 2023
Topic Review
3D Photorealistic Human Body Modelling and Reconstruction Techniques
The continuous evolution of video technologies is now primarily focused on enhancing 3D video paradigms and consistently improving their quality, realism, and level of immersion. Both the research community and the industry work towards improving 3D content representation, compression, and transmission. Their collective efforts culminate in the striving for real-time transfer of volumetric data between distant locations, laying the foundation for holographic-type communication (HTC). 
  • 242
  • 21 Nov 2023
Topic Review
From Shallow to Deep Bioprocess Hybrid Modeling
Hybrid neural network (HNN)  modeling is the combination of artificial neural networks (ANNs) with prior knowledge in a mathematical framework. There are two main approaches to incorporating prior knowledge: design and training methods. Design approaches use prior knowledge to define the network structure, while training approaches use it to guide parameter estimation. Both approaches reduce data dependency, making models less sensitive to sparse and noisy data, and improving their descriptive and predictive capabilities compared to pure ANNs. HNNs are a powerful tool for understanding complex processes like bioprocesses and accelerating product development. Bioprocess modeling is challenging due to nonlinearity, dynamics, and uncertainty. Traditional models based on physical and chemical laws can be overly simplistic or hard to calibrate. Data-driven ANN models lack interpretability and generalization. HNNs combine the strengths of both approaches, enhancing the accuracy, robustness, and efficiency of bioprocess modeling by integrating prior knowledge with ANNs.
  • 159
  • 20 Nov 2023
Topic Review
Implementation of Location-Based Game Prototypes
Location-based games (LBGs) are a form of experimentation with locative media involving location-aware mobile technologies and the disclosure of user locations. By integrating digital content with physical space through GPS technology, a hybrid space is created, offering a multi-dimensional experience. Locative games exemplify the ludic trend in contemporary culture. The use of locative media further enriches urban spaces by providing location-based information and hidden narratives. These developments originated from artistic experimentation with GPS technology, since artists explored hybrid spaces by integrating data packets or metadata into physical environments.
  • 246
  • 17 Nov 2023
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