Introduction: Streaming services are highly popular today. Millions of people watch live streams or videos and listen to music.
Methods: One of the most popular streaming platforms is Twitch, and data from this type of service can be a good example for applying the parallel DBSCAN algorithm proposed in this paper. Unlike the classical approach to neighbor search, the proposed one avoids redundancy, i.e., the repetition of the same calculations. At the same time, this algorithm is based on the classical DBSCAN method with a full search for all neighbors, parallelization by subtasks, and OpenMP parallel computing technology.
Results: In this work, without reducing the accuracy, we managed to speed up the solution based on the DBSCAN algorithm when analyzing medium-sized data. As a result, the acceleration rate tends to the number of cores of a multicore computer system and the efficiency to one.
Discussion: Before conducting numerical experiments, theoretical estimates of speed-up and efficiency were obtained, and they aligned with the results obtained, confirming their validity. The quality of the performed clustering was verified using the silhouette value. All experiments were conducted using different percentages of medium-sized datasets. The prospects of applying the proposed algorithm can be obtained in various fields such as advertising, marketing, cybersecurity, and sociology. It is worth mentioning that datasets of this kind are often used for detecting fraud on the Internet, making an algorithm capable of considering all neighbors a useful tool for such research.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10644222 | PMC |
| http://dx.doi.org/10.3389/fdata.2023.1292923 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Clustering Cu-S based compounds using periodic table representation and compositional Wasserstein distance.
Sci Rep
December 2024
Key Laboratory of Computing Power Network and Information Security, Shandong Computer Science Center (National Supercomputing Center in Jinan), Ministry of Education, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250013, Shandong, P. R. China.
Crystal structure similarity is useful for the chemical analysis of nowadays big materials databases and data mining new materials. Here we propose to use two-dimensional Wasserstein distance (earth mover's distance) to measure the compositional similarity between different compounds, based on the periodic table representation of compositions. To demonstrate the effectiveness of our approach, 1586 Cu-S based compounds are taken from the inorganic crystal structure database (ICSD) to form a validation dataset.
View Article and Find Full Text PDFResearch on Multimodal Control Method for Prosthetic Hands Based on Visuo-Tactile and Arm Motion Measurement.
Biomimetics (Basel)
December 2024
Institute of Instrument Science and Engineering, Southeast University, Nanjing 210096, China.
Article Synopsis
- The research focuses on enhancing robotic hand function to assist disabled individuals, leveraging advanced multimodal perception and control methods.
- Key techniques include using a pinhole camera and YOLOv8 for object recognition, along with multi-frame data and clustering algorithms to ensure accurate grasping by the robotic hand.
- The resulting system achieves a high grasping success rate of 91.63% while maintaining user comfort, demonstrating its effectiveness and potential for real-world application.
: A Python Package for Polymer Chain Orientation and Microstructure Evolution Monitoring.
J Chem Theory Comput
December 2024
Mechanical and Industrial Engineering Department, Northeastern University, Boston, Massachusetts 02115, United States.
In the pursuit of informing experimental techniques with in silico optimizations, we propose a pip deployable Python package, , to easily determine polymer crystallites within molecular dynamic melts and the chain orientation parameters of atomistic and coarse-grained simulations. The package supports the commonly used ⟨⟩, ⟨⟩, and ⟨⟩ order parameters based on the chain chord vector and utilizes a modified DBSCAN algorithm to determine crystalline regions. The results of analysis are written to text and LAMMPS dump files for visualization and analysis.
View Article and Find Full Text PDFA novel machine learning model for perimeter intrusion detection using intrusion image dataset.
PLoS One
December 2024
Computer Science Academic Group, Faculty of Information and Communication Technology, Mahidol University, Salaya, Nakhon Pathom, Thailand.
Perimeter Intrusion Detection Systems (PIDS) are crucial for protecting any physical locations by detecting and responding to intrusions around its perimeter. Despite the availability of several PIDS, challenges remain in detection accuracy and precise activity classification. To address these challenges, a new machine learning model is developed.
View Article and Find Full Text PDFReal-Time Radar Classification Based on Software-Defined Radio Platforms: Enhancing Processing Speed and Accuracy with Graphics Processing Unit Acceleration.
Sensors (Basel)
December 2024
Department of Electronic Systems, Norwegian University of Science and Technology, 2815 Gjovik, Norway.
This paper presents a comprehensive evaluation of real-time radar classification using software-defined radio (SDR) platforms. The transition from analog to digital technologies, facilitated by SDR, has revolutionized radio systems, offering unprecedented flexibility and reconfigurability through software-based operations. This advancement complements the role of radar signal parameters, encapsulated in the pulse description words (PDWs), which play a pivotal role in electronic support measure (ESM) systems, enabling the detection and classification of threat radars.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!