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Topic Review
k-NN Query for High-Dimensional Index Using Machine Learning
The three k-nearest neighbor (k-NN) optimization techniques for a distributed, in-memory-based, high-dimensional indexing method to speed up content-based image retrieval. The techniques perform distributed, in-memory, high-dimensional indexing-based k-NN query optimization: a density-based optimization technique that performs k-NN optimization using data distribution; a cost-based optimization technique using query processing cost statistics; and a learning-based optimization technique using a deep learning model, based on query logs.
  • 263
  • 08 Jun 2023
Topic Review
New Semantic Segmentation Method for Remote Sensing Images
Semantic segmentation is an important task for the interpretation of remote sensing images. Remote sensing images are large in size, contain substantial spatial semantic information, and generally exhibit strong symmetry, resulting in images exhibiting large intraclass variance and small interclass variance, thus leading to class imbalance and poor small-object segmentation.
  • 259
  • 08 Jun 2023
Topic Review
Deepfake Identification and Traceability
Researchers and companies have released multiple datasets of face deepfakes labeled to indicate different methods of forgery. Naming these labels is often arbitrary and inconsistent. However, researchers must use multiple datasets in practical applications to conduct traceability research. The researchers utilize the K-means clustering method to identify datasets with similar feature values and analyze the feature values using the Calinski Harabasz Index method. Datasets with the same or similar labels in different deepfake datasets exhibit different forgery features. The KCE system can solve this problem, which combines multiple deepfake datasets according to feature similarity. In the model trained based on KCE combined data, the Calinski Harabasz scored 42.3% higher than the combined data by the same forgery name. It shows that this method improves the generalization ability of the model.
  • 461
  • 08 Jun 2023
Topic Review
AI-Based Unmanned Aerial Vehicles Networks
To enhance the overall performance of the unmanned aerial vehicles (UAVs) networks and to address some specific problems, new features in the network are being designed as autonomous features. This approach not only provides optimum solutions for the targeted problems but also supports the dynamic properties of a UAV network. 
  • 268
  • 07 Jun 2023
Topic Review
Decomposition for Multivariant Traffic Time Series
Data-driven modeling methods have been widely used in many applications or studies of traffic systems with complexity and chaos. The empirical mode decomposition (EMD) family provides a lightweight analytical method for non-stationary and non-linear data.  A large amount of traffic data in practice are usually multidimensional, so the EMD family cannot be used directly for those data.
  • 206
  • 07 Jun 2023
Topic Review
Blockchain-Based Loyalty Programs
Loyalty platforms are designed to increase customer loyalty and thus increase consumers’ attraction to purchase. Loyalty programs are one of the main options for brands to increase their accessibility and attractiveness. However, these systems have shortcomings that can influence interaction with users. Blockchain is an innovative technology capable of transforming the behavior of these systems and solving current problems.
  • 608
  • 07 Jun 2023
Topic Review
Simulation of Light Scattering in Automotive Paints
Modern automotive paints are of great interest in research works. They contain colorant particles and thin flat metallic or pearlescent flakes distributed in a clear varnish. There are two main approaches to simulation of light scattering in a dispersed media. The first one is based on the continuous medium model. This model is faster but less accurate. The second approach is the simulation of light propagation through an ensemble of paint flakes and particles represented as an explicit geometry. This model correctly calculates light scattering but is rather time-consuming.
  • 502
  • 07 Jun 2023
Topic Review
Machine Learning-based Driver Drowsiness Detection Using Visual Features
Drowsiness-related car accidents continue to have a significant effect on road safety. Many of these accidents can be eliminated by alerting the drivers once they start feeling drowsy. Image-based systems are the most commonly used techniques for detecting driver drowsiness. Facial parameters such as the eyes, mouth, and head can be used to identify many visual behaviors that fatigued people exhibit.
  • 434
  • 06 Jun 2023
Topic Review
Blockchain-Based AuthenticationProtocol Design
The HIDA protocol we proposed is a secure and efficient identity verification protocol in cloud computing environments. The protocol uses federated chain technology to securely isolate entities in the trust domain, and combines zero-knowledge proof technology to further protect user data. Federated chain technology isolates interaction between different entities in their respective chains, achieving secure data isolation. Zero-knowledge proof technology can prove user identity information without revealing their true identity. Subsequent access management allows users to prove their identity with a brief credential, greatly improving access efficiency. We conducted formal semantic analysis and simulations, proving the protocol's high efficiency and reliability in practical applications. These research results provide new ideas and technical support for identity verification in cloud environments, providing valuable references for achieving more secure and efficient cloud computing application scenarios.
  • 296
  • 06 Jun 2023
Topic Review
Negotiation Protocol with Pre-Domain Narrowing
Consensus building among agents is crucial in multi-agent system because each agent acts independently according to its utility function, and conflict among agents can occur. Therefore, automated negotiation is an essential technology for efficiently resolving conflicts and forming consensuses while also keeping agents' privacy. As the domain to be negotiated is large, the computational cost of reaching a consensus increases and the agreement rate decreases. Some negotiation protocols have been proposed wherein a mediator collects the utility information of each agent and creates multiple alternatives of agreements to handle large-scale multi-issue negotiations. However, in such protocols, a limitation is placed on agents' privacy because all agents have to disclose their private information by following the mediator and predecided negotiation rules.
  • 240
  • 05 Jun 2023
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