Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Multimachine Stability01:25

Multimachine Stability

230
Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
230
Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

181
The maximum power flow for lossy transmission lines is derived using ABCD parameters in phasor form. These parameters create a matrix relationship between the sending-end and receiving-end voltages and currents, allowing the determination of the receiving-end current. This relationship facilitates calculating the complex power delivered to the receiving end, from which real and reactive power components are derived.
181
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

101
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
101
Response Surface Methodology01:16

Response Surface Methodology

267
Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:
267
The Power Flow Problem and Solution01:26

The Power Flow Problem and Solution

341
Power flow problem analysis is fundamental for determining real and reactive power flows in network components, such as transmission lines, transformers, and loads. The power system's single-line diagram provides data on the bus, transmission line, and transformer. Each bus k in the system is characterized by four key variables: voltage magnitude Vk​, phase angle δk​, real power Pk​, and reactive power Qk​. Two of these four variables are inputs, while the...
341
Simplified Synchronous Machine Model01:30

Simplified Synchronous Machine Model

332
The Synchronous Machine Model is a fundamental tool in analyzing and ensuring the transient stability of power systems. This model simplifies the representation of a synchronous machine under balanced three-phase positive-sequence conditions, assuming constant excitation and ignoring losses and saturation. The model is pivotal for understanding the behavior of synchronous generators connected to a power grid, particularly during transient events.
In this model, each generator is connected to a...
332

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Quantifying institutional gender inequality in contemporary visual art.

Nature communications·2026
Same author

Coupled metabolic and endocrine dysregulation underlies the intergenerational toxicity of BPTMC: Insights from sex-specific transmission.

Journal of hazardous materials·2026
Same author

Preoperative Nonpharmacological Anxiety Management in Adult Ophthalmic Surgery: A Scoping Review.

Journal of perianesthesia nursing : official journal of the American Society of PeriAnesthesia Nurses·2026
Same author

First dermoscopic characterization and histopathological correlation of panfolliculoma: a case report and review of the literature.

Frontiers in medicine·2026
Same author

Orbital hybridization-mediated nanozymes reverse cellular senescence for aged bone regeneration.

Biomaterials·2026
Same author

Ocular Residual Astigmatism, Posterior Corneal Astigmatism, and Anterior Corneal Irregularities in Virgin Eyes Undergoing Topography-guided LASIK.

Journal of refractive surgery (Thorofare, N.J. : 1995)·2026

Related Experiment Video

Updated: Sep 13, 2025

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

523

Jointly Optimizing Resource Allocation, User Scheduling, and Grouping in SBMA Networks: A PSO Approach.

Jianjian Wu1,2,3, Chanzi Liu2,3,4, Xindi Wang5

  • 1The School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230601, China.

Entropy (Basel, Switzerland)
|July 29, 2025
PubMed
Summary
This summary is machine-generated.

A new Sparsecode-and-BIA-based Multiple Access (SBMA) scheme combines Blind Interference Alignment and Sparse Code Multiple Access for massive connectivity. An optimized algorithm significantly improves the number of users meeting Quality of Service demands.

Keywords:
blind interference alignment (BIA)multiple accesssparse-code multiple access (SCMA)

More Related Videos

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

661
Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.0K

Related Experiment Videos

Last Updated: Sep 13, 2025

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

523
Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

661
Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.0K

Area of Science:

  • Wireless communication systems
  • Signal processing for telecommunications
  • Network resource management

Background:

  • Blind Interference Alignment (BIA) and Sparse Code Multiple Access (SCMA) enable massive connectivity but have limitations.
  • The proposed Sparsecode-and-BIA-based Multiple Access (SBMA) scheme integrates BIA and SCMA strengths for improved performance.
  • SBMA utilizes flexible user grouping (UG) to manage sparse code constraints and interference alignment for diverse Quality of Service (QoS) demands.

Purpose of the Study:

  • To address the challenge of efficient joint resource allocation (RA), user scheduling (US), and user grouping (UG) in SBMA systems.
  • To develop an algorithm capable of optimizing RA, US, and UG for SBMA, overcoming limitations of existing SCMA or BIA solutions.
  • To maximize the number of users meeting QoS requirements within the SBMA framework.

Main Methods:

  • Formulation of the joint RA, US, and UG problem for SBMA as an integer optimization task.
  • Development of a Particle Swarm Optimization (PSO)-based algorithm with a specialized update function for joint US and UG decisions.
  • Comprehensive simulations to evaluate the proposed algorithm's performance against random-based schemes.

Main Results:

  • The proposed PSO-based algorithm significantly outperforms random-based schemes in SBMA systems.
  • Under specific conditions, the algorithm achieves approximately 280% higher user satisfaction (meeting QoS requirements) in high-SNR scenarios.
  • Demonstrates the effectiveness of joint optimization for resource allocation, user scheduling, and user grouping in SBMA.

Conclusions:

  • The developed PSO algorithm provides an effective solution for the complex joint RA, US, and UG problem in SBMA.
  • SBMA, when optimized with the proposed algorithm, offers substantial improvements in supporting massive connectivity with diverse QoS demands.
  • This work highlights the critical need for tailored optimization techniques for hybrid access schemes like SBMA.